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value="clinpract" > Clinics and Practice </option> <option value="clockssleep" > Clocks & Sleep </option> <option value="coasts" > Coasts </option> <option value="coatings" > Coatings </option> <option value="colloids" > Colloids and Interfaces </option> <option value="colorants" > Colorants </option> <option value="commodities" > Commodities </option> <option value="complications" > Complications </option> <option value="compounds" > Compounds </option> <option value="computation" > Computation </option> <option value="csmf" > Computer Sciences & Mathematics Forum </option> <option value="computers" > Computers </option> <option value="condensedmatter" > Condensed Matter </option> <option value="conservation" > Conservation </option> <option value="constrmater" > Construction Materials </option> <option value="cmd" > Corrosion and Materials Degradation (CMD) </option> <option value="cosmetics" > Cosmetics </option> <option value="covid" > COVID </option> <option value="crops" > Crops </option> <option value="cryo" > Cryo </option> <option value="cryptography" > Cryptography </option> <option value="crystals" > Crystals </option> <option value="cimb" > Current Issues in Molecular Biology (CIMB) </option> <option value="curroncol" > Current Oncology </option> <option value="dairy" > Dairy </option> <option value="data" > Data </option> <option value="dentistry" > Dentistry Journal </option> <option value="dermato" > Dermato </option> <option value="dermatopathology" > Dermatopathology </option> <option value="designs" > Designs </option> <option value="diabetology" > Diabetology </option> <option value="diagnostics" > Diagnostics </option> <option value="dietetics" > Dietetics </option> <option value="digital" > Digital </option> <option value="disabilities" > Disabilities </option> <option value="diseases" > Diseases </option> <option value="diversity" > Diversity </option> <option value="dna" > DNA </option> <option value="drones" > Drones </option> <option value="ddc" > Drugs and Drug Candidates (DDC) </option> <option value="dynamics" > Dynamics </option> <option value="earth" > Earth </option> <option value="ecologies" > Ecologies </option> <option value="econometrics" > Econometrics </option> <option value="economies" > Economies </option> <option value="education" > Education Sciences </option> <option value="electricity" > Electricity </option> <option value="electrochem" > Electrochem </option> <option value="electronicmat" > Electronic Materials </option> <option value="electronics" > Electronics </option> <option value="ecm" > Emergency Care and Medicine </option> <option value="encyclopedia" > Encyclopedia </option> <option value="endocrines" > Endocrines </option> <option value="energies" > Energies </option> <option value="esa" > Energy Storage and Applications (ESA) </option> <option value="eng" > Eng </option> <option value="engproc" > Engineering Proceedings </option> <option value="entropy" > Entropy </option> <option value="environsciproc" > Environmental Sciences Proceedings </option> <option value="environments" > Environments </option> <option value="epidemiologia" > Epidemiologia </option> <option value="epigenomes" > Epigenomes </option> <option value="ebj" > European Burn Journal (EBJ) </option> <option value="ejihpe" > European Journal of Investigation in Health, Psychology and Education (EJIHPE) </option> <option value="fermentation" > Fermentation </option> <option value="fibers" > Fibers </option> <option value="fintech" > FinTech </option> <option value="fire" > Fire </option> <option value="fishes" > Fishes </option> <option value="fluids" > Fluids </option> <option value="foods" > Foods </option> <option value="forecasting" > Forecasting </option> <option value="forensicsci" > Forensic Sciences </option> <option value="forests" > Forests </option> <option value="fossstud" > Fossil Studies </option> <option value="foundations" > Foundations </option> <option value="fractalfract" > Fractal and Fractional (Fractal Fract) </option> <option value="fuels" > Fuels </option> <option value="future" > Future </option> <option value="futureinternet" > Future Internet </option> <option value="futurepharmacol" > Future Pharmacology </option> <option value="futuretransp" > Future Transportation </option> <option value="galaxies" > Galaxies </option> <option value="games" > Games </option> <option value="gases" > Gases </option> <option value="gastroent" > Gastroenterology Insights </option> <option value="gastrointestdisord" > Gastrointestinal Disorders </option> <option value="gastronomy" > Gastronomy </option> <option value="gels" > Gels </option> <option value="genealogy" > Genealogy </option> <option value="genes" > Genes </option> <option value="geographies" > Geographies </option> <option value="geohazards" > GeoHazards </option> <option value="geomatics" > Geomatics </option> <option value="geometry" > Geometry </option> <option value="geosciences" > Geosciences </option> <option value="geotechnics" > Geotechnics </option> <option value="geriatrics" > Geriatrics </option> <option value="glacies" > Glacies </option> <option value="gucdd" > Gout, Urate, and Crystal Deposition Disease (GUCDD) </option> <option value="grasses" > Grasses </option> <option value="hardware" > Hardware </option> <option value="healthcare" > Healthcare </option> <option value="hearts" > Hearts </option> <option value="hemato" > Hemato </option> <option value="hematolrep" > Hematology Reports </option> <option value="heritage" > Heritage </option> <option value="histories" > Histories </option> <option value="horticulturae" > Horticulturae </option> <option value="hospitals" > Hospitals </option> <option value="humanities" > Humanities </option> <option value="humans" > Humans </option> <option value="hydrobiology" > Hydrobiology </option> <option value="hydrogen" > Hydrogen </option> <option value="hydrology" > Hydrology </option> <option value="hygiene" > Hygiene </option> <option value="immuno" > Immuno </option> <option value="idr" > Infectious Disease Reports </option> <option value="informatics" > Informatics </option> <option value="information" > Information </option> <option value="infrastructures" > Infrastructures </option> <option value="inorganics" > Inorganics </option> <option value="insects" > Insects </option> <option value="instruments" > Instruments </option> <option value="iic" > Intelligent Infrastructure and Construction </option> <option value="ijerph" > International Journal of Environmental Research and Public Health (IJERPH) </option> <option value="ijfs" > International Journal of Financial Studies (IJFS) </option> <option value="ijms" > International Journal of Molecular Sciences (IJMS) </option> <option value="IJNS" > International Journal of Neonatal Screening (IJNS) </option> <option value="ijpb" > International Journal of Plant Biology (IJPB) </option> <option value="ijt" > International Journal of Topology 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Intell.) </option> <option value="jlpea" > Journal of Low Power Electronics and Applications (JLPEA) </option> <option value="jmmp" > Journal of Manufacturing and Materials Processing (JMMP) </option> <option value="jmse" > Journal of Marine Science and Engineering (JMSE) </option> <option value="jmahp" > Journal of Market Access & Health Policy (JMAHP) </option> <option value="jmp" > Journal of Molecular Pathology (JMP) </option> <option value="jnt" > Journal of Nanotheranostics (JNT) </option> <option value="jne" > Journal of Nuclear Engineering (JNE) </option> <option value="ohbm" > Journal of Otorhinolaryngology, Hearing and Balance Medicine (JOHBM) </option> <option value="jop" > Journal of Parks </option> <option value="jpm" > Journal of Personalized Medicine (JPM) </option> <option value="jpbi" > Journal of Pharmaceutical and BioTech Industry (JPBI) </option> <option value="jor" > Journal of Respiration (JoR) </option> <option value="jrfm" > Journal of Risk and Financial Management (JRFM) </option> <option value="jsan" > Journal of Sensor and Actuator Networks (JSAN) </option> <option value="joma" > Journal of the Oman Medical Association (JOMA) </option> <option value="jtaer" > Journal of Theoretical and Applied Electronic Commerce Research (JTAER) </option> <option value="jvd" > Journal of Vascular Diseases (JVD) </option> <option value="jox" > Journal of Xenobiotics (JoX) </option> <option value="jzbg" > Journal of Zoological and Botanical Gardens (JZBG) </option> <option value="journalmedia" > Journalism and Media </option> <option value="kidneydial" > Kidney and Dialysis </option> <option value="kinasesphosphatases" > Kinases and Phosphatases </option> <option value="knowledge" > Knowledge </option> <option value="labmed" > LabMed </option> <option value="laboratories" > Laboratories </option> <option value="land" > Land </option> <option value="languages" > Languages </option> <option value="laws" > Laws </option> <option value="life" > Life 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Pharm.) </option> <option value="sclerosis" > Sclerosis </option> <option value="seeds" > Seeds </option> <option value="sensors" > Sensors </option> <option value="separations" > Separations </option> <option value="sexes" > Sexes </option> <option value="signals" > Signals </option> <option value="sinusitis" > Sinusitis </option> <option value="smartcities" > Smart Cities </option> <option value="socsci" > Social Sciences </option> <option value="siuj" > Soci茅t茅 Internationale d鈥橴rologie Journal (SIUJ) </option> <option value="societies" > Societies </option> <option value="software" > Software </option> <option value="soilsystems" > Soil Systems </option> <option value="solar" > Solar </option> <option value="solids" > Solids </option> <option value="spectroscj" > Spectroscopy Journal </option> <option value="sports" > Sports </option> <option value="standards" > Standards </option> <option value="stats" > Stats </option> <option value="stresses" > Stresses </option> <option value="surfaces" > Surfaces </option> <option value="surgeries" > Surgeries </option> <option value="std" > Surgical Techniques Development </option> <option value="sustainability" > Sustainability </option> <option value="suschem" > Sustainable Chemistry </option> <option value="symmetry" > Symmetry </option> <option value="synbio" > SynBio </option> <option value="systems" > Systems </option> <option value="targets" > Targets </option> <option value="taxonomy" > Taxonomy </option> <option value="technologies" > Technologies </option> <option value="telecom" > Telecom </option> <option value="textiles" > Textiles </option> <option value="thalassrep" > Thalassemia Reports </option> <option value="therapeutics" > Therapeutics </option> <option value="thermo" > Thermo </option> <option value="timespace" > Time and Space </option> <option value="tomography" > Tomography </option> <option value="tourismhosp" > Tourism and Hospitality </option> <option value="toxics" > Toxics </option> 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value="women" > Women </option> <option value="world" > World </option> <option value="wevj" > World Electric Vehicle Journal (WEVJ) </option> <option value="youth" > Youth </option> <option value="zoonoticdis" > Zoonotic Diseases </option> </select> </div> <div class="large-2 medium-2 small-6 columns "> <div class=""> <div class="search-input-label">Article Type</div> </div> <select id="article_type" tabindex="4" name="article_type" class="chosen-select"> <option value="">All Article Types</option> <option value="research-article">Article</option> <option value="review-article">Review</option> <option value="rapid-communication">Communication</option> <option value="editorial">Editorial</option> <option value="abstract">Abstract</option> <option value="book-review">Book Review</option> <option value="brief-communication">Brief Communication</option> <option value="brief-report">Brief Report</option> <option value="case-report">Case Report</option> <option 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class="custom-accordion-for-small-screen-link " > <h2>Saved Queries</h2> </div> <div class="target-item custom-accordion-for-small-screen-content show-for-medium-up"> <div class="generic-item refind-item-wrap no-border last-item no-padding-top"> <a class="bold" href="/user/login">Sign in</a> to use this feature. </div> </div> </div> <div class="content__container " > <div class="custom-accordion-for-small-screen-link " data-callback=processResetAllVisibility> <h2> Search Filter <a href="#" class="remove-refines remove-refines-all link--red right">Reset All</a> </h2> </div> <div class="target-item custom-accordion-for-small-screen-content show-for-medium-up"> <div class="generic-item refind-item-wrap no-border no-padding-top"> <h3>Years</h3> <span>Between:</span> <input type="number" id="refine_year_from" style="display: inline-block; font-size: 12px;" name="year_from" value="1996" min="1996" max="2024"> - <input type="number" id="refine_year_to" style="display: inline-block; font-size: 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data-filterid="refine_subjects_computer-math"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computer Science & Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_business-econ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Business & Economics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_environment"> <i class="material-icons">remove_circle_outline</i> </a> <label> Environmental & Earth Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_physics-astronomy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Physical Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_arts-humanity"> <i class="material-icons">remove_circle_outline</i> </a> <label> Social Sciences, Arts and Humanities </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_engineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_chem-materials"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemistry & Materials Science </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_health"> <i class="material-icons">remove_circle_outline</i> </a> <label> Public Health & Healthcare </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_bio-life"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biology & Life Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_med-pharma"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medicine & Pharmacology </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-subjects" data-filter="subjects"><strong>Add Subjects</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="subjects"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-subjects" data-filter="subjects" class="all">Select Subjects</a> </div> <div style="clear:both;"></div> <div id="refine-modal-subjects" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Subjects</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Subjects" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select subjects you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="computer science & mathematics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_computer-math" value="computer-math"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_computer-math">Computer Science & Mathematics (1450)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="business & economics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_business-econ" value="business-econ"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_business-econ">Business & Economics (1382)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="environmental & earth sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_environment" value="environment"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_environment">Environmental & Earth Sciences (780)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="physical sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_physics-astronomy" value="physics-astronomy"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_physics-astronomy">Physical Sciences (552)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="social sciences, arts and humanities" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_arts-humanity" value="arts-humanity"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_arts-humanity">Social Sciences, Arts and Humanities (509)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="engineering" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_engineering" value="engineering"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_engineering">Engineering (478)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="chemistry & materials science" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_chem-materials" value="chem-materials"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_chem-materials">Chemistry & Materials Science (374)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="public health & healthcare" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_health" value="health"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_health">Public Health & Healthcare (283)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="biology & life sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_bio-life" value="bio-life"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_bio-life">Biology & Life Sciences (180)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="medicine & pharmacology" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_med-pharma" value="med-pharma"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_med-pharma">Medicine & Pharmacology (63)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="subjects" onclick="$('#refine-modal-subjects').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="subjects" id="refine_subjects_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-journals" style=""> <h3>Journals</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sustainability"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sustainability </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jrfm"> <i class="material-icons">remove_circle_outline</i> </a> <label> JRFM </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mathematics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijfs"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJFS </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_entropy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Entropy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_risks"> <i class="material-icons">remove_circle_outline</i> </a> <label> Risks </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_energies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Energies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_economies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Economies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_applsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Applied Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijerph"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJERPH </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_electronics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Electronics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_forests"> <i class="material-icons">remove_circle_outline</i> </a> <label> Forests </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_symmetry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Symmetry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_information"> <i class="material-icons">remove_circle_outline</i> </a> <label> Information </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_axioms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Axioms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_econometrics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Econometrics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fractalfract"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fractal Fract </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_systems"> <i class="material-icons">remove_circle_outline</i> </a> <label> Systems </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_animals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Animals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_engproc"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_buildings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Buildings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_futureinternet"> <i class="material-icons">remove_circle_outline</i> </a> <label> Future Internet </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_admsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Administrative Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sensors"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sensors </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_algorithms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Algorithms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_water"> <i class="material-icons">remove_circle_outline</i> </a> <label> Water </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_land"> <i class="material-icons">remove_circle_outline</i> </a> <label> Land </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_agriculture"> <i class="material-icons">remove_circle_outline</i> </a> <label> Agriculture </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_forecasting"> <i class="material-icons">remove_circle_outline</i> </a> <label> Forecasting </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_data"> <i class="material-icons">remove_circle_outline</i> </a> <label> Data </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_fishes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fishes </label> 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onclick="$('#refine-modal-article_types').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="article_types" id="refine_article_types_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-countries" style=""> <h3>Countries / Regions</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> China </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_STATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> USA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KOREA_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Republic of Korea </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_KINGDOM"> <i class="material-icons">remove_circle_outline</i> </a> <label> UK </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SPAIN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Spain </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ITALY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Italy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TAIWAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Taiwan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_POLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Poland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRALIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Australia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PAKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pakistan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SAUDI_ARABIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Saudi Arabia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> India </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ROMANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Romania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MALAYSIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Malaysia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GERMANY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Germany </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JAPAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Japan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PORTUGAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Portugal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SOUTH_AFRICA"> <i class="material-icons">remove_circle_outline</i> </a> <label> South Africa </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CANADA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Canada </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_VIETNAM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vietnam </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FRANCE"> <i class="material-icons">remove_circle_outline</i> </a> <label> France </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDONESIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Indonesia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TURKEY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Turkey (T眉rkiye) </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GREECE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Greece </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BRAZIL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brazil </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_RUSSIAN_FEDERATION"> <i class="material-icons">remove_circle_outline</i> </a> <label> Russia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_ARAB_EMIRATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> United Arab Emirates </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_THAILAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Thailand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAN_ISLAMIC_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iran </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NETHERLANDS"> <i class="material-icons">remove_circle_outline</i> </a> <label> The Netherlands </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NEW_ZEALAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> New Zealand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_HUNGARY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hungary </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BANGLADESH"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bangladesh </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_EGYPT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Egypt </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHILE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chile </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MEXICO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mexico </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TUNISIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tunisia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BELGIUM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Belgium </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NORWAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Norway </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JORDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Jordan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MOROCCO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Morocco </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWITZERLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Switzerland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CROATIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Croatia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CZECH_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Czech Republic </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_COLOMBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Colombia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWEDEN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sweden </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Austria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_DENMARK"> <i class="material-icons">remove_circle_outline</i> </a> <label> Denmark </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FINLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Finland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_HONG_KONG"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hong Kong </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SERBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Serbia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRELAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ireland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SINGAPORE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Singapore </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BAHRAIN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bahrain </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GHANA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ghana </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ISRAEL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Israel </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NIGERIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nigeria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_QATAR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Qatar </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVAKIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovakia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MALTA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Malta </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KUWAIT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kuwait </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LEBANON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lebanon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LITHUANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lithuania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_OMAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Oman </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BOSNIA_AND_HERZEGOVINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bosnia and Herzegovina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ECUADOR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ecuador </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_YEMEN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Yemen </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BRUNEI"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brunei </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BULGARIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bulgaria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CYPRUS"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cyprus </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ESTONIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Estonia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAQ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iraq </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KAZAKHSTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kazakhstan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LATVIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Latvia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AZERBAIJAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Azerbaijan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ICELAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iceland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PERU"> <i class="material-icons">remove_circle_outline</i> </a> <label> Peru </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PHILIPPINES"> <i class="material-icons">remove_circle_outline</i> </a> <label> Philippines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UKRAINE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ukraine </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_URUGUAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uruguay </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ALBANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Albania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KENYA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kenya </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PANAMA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Panama </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVENIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovenia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SRI_LANKA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sri Lanka </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SUDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sudan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TANZANIA_UNITED_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tanzania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TIMOR-LESTE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Timor-Leste </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ARGENTINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Argentina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ARMENIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Armenia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BOLIVIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bolivia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CAMEROON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cameroon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_COSTA_RICA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Costa Rica </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ETHIOPIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ethiopia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FIJI"> <i class="material-icons">remove_circle_outline</i> </a> <label> Fiji </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LAO_PEOPLES_DEMOCRATIC_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Laos </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MACAO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Macao </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MAURITIUS"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mauritius </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MONGOLIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mongolia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MOZAMBIQUE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mozambique </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NAMIBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Namibia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NEPAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nepal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SENEGAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Senegal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SYRIAN_ARAB_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Syrian Arab Republic </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UZBEKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uzbekistan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_VENEZUELA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Venezuela </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ZAMBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Zambia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ZIMBABWE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Zimbabwe </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PALESTINE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Palestine </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_Kosovo"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kosovo </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MONTENEGRO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Montenegro </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-countries" data-filter="countries"><strong>Add Countries / Regions</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="countries"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-countries" data-filter="countries" class="all">Select Countries / Regions</a> </div> <div style="clear:both;"></div> <div id="refine-modal-countries" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Countries / Regions</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Countries / Regions" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select countries / regions you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="china" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CHINA" value="CHINA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CHINA">China (468)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="usa" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UNITED_STATES" value="UNITED_STATES"> 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data-filter="united arab emirates" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UNITED_ARAB_EMIRATES" value="UNITED_ARAB_EMIRATES"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UNITED_ARAB_EMIRATES">United Arab Emirates (36)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="thailand" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_THAILAND" value="THAILAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_THAILAND">Thailand (35)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="iran" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" 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class="refine_checkbox refine_countries" id="refine_countries_SERBIA" value="SERBIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SERBIA">Serbia (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="ireland" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_IRELAND" value="IRELAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_IRELAND">Ireland (10)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="singapore" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SINGAPORE" value="SINGAPORE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SINGAPORE">Singapore 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> <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ECUADOR" value="ECUADOR"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ECUADOR">Ecuador (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="yemen" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_YEMEN" value="YEMEN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_YEMEN">Yemen (5)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="brunei" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_BRUNEI" value="BRUNEI"> <label class="search_refine_label" style="margin-bottom: 10px;" 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padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ICELAND" value="ICELAND"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ICELAND">Iceland (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="peru" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PERU" value="PERU"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_PERU">Peru (3)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="philippines" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_PHILIPPINES" value="PHILIPPINES"> <label class="search_refine_label" 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value="1527247" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 284 KiB   </span> <a href="/2410-3888/9/12/472/pdf?version=1732282809" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="When Mediterranean Artisanal Fishers Protect Coastal Ecosystems" data-journal="fishes"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Brief Report</span></div> <a class="title-link" href="/2410-3888/9/12/472">When Mediterranean Artisanal Fishers Protect Coastal Ecosystems</a> <div class="authors"> by <span class="inlineblock "><strong>Cornelia E. Nauen</strong></span> </div> <div class="color-grey-dark"> <em>Fishes</em> <b>2024</b>, <em>9</em>(12), 472; <a href="https://doi.org/10.3390/fishes9120472">https://doi.org/10.3390/fishes9120472</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> According to EuroStat data, the recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. This gradual decline slowed after the entering into force of the reform of the <a href="#" data-counterslink = "https://www.mdpi.com/2410-3888/9/12/472/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> According to EuroStat data, the recorded landings of fisheries products from European waters were estimated at about 6 million tons in 2001, down to 3.2 million tons in 2022. This gradual decline slowed after the entering into force of the reform of the European Common Fisheries Policy (CFP) at the end of 2013, but was followed by a steeper decline after 2018. This is reflected in the last assessment of the Scientific Technical and Economic Committee for Fisheries (STEPF), noting that despite progress in the NE Atlantic management, 41% of the assessed stocks in 2022 were outside safe biological limits, down from 80% in 2003. Improvements in the Mediterranean are significantly slower. A warming ocean provokes the measurable poleward migration of species and adds stress to predator–prey relations in all European seas. Within this general picture, the broad-brush landscape is influenced by policy applications more in favour of industrial exploitation and regulatory and market environments, making it very hard for many small-scale fishers (SSFs) to remain in business, let alone attract younger successors for generational transition. In crowded marine spaces, it is a challenge to allocate access rights fairly between fisheries, exclusion zones for resource and habitat protection and much-needed ecosystem recovery, platforms for fossil exploitation, wind farms, underwater cables and recreational uses. Two examples of local initiatives with faunal recovery potential in the Mediterranean are briefly presented as a bottom-up complement to more top-down management approaches. They are spearheaded by artisanal fishers, who seek to restore spawning grounds and other coastal habitats as a way to procure enough fish and other complementary activities to secure their livelihoods in the future. They are supported by local scientists and nature conservation organisations. While promising, this is still rather the exception. Here, it is argued that trust-building between artisanal fishers, conservationists and scientists, and greater systemic support to SSFs by governments, increase chances for the urgently needed structural shifts that deliver the reversal in the ongoing decline in biodiversity and ocean productivity that all aspire to, to ensure sustained social and economic benefits. <a href="/2410-3888/9/12/472">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/fishes/special_issues/CLN21ALD90 ">Fisheries Policies and Management</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1527108" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 320 KiB   </span> <a href="/1911-8074/17/12/530/pdf?version=1732275775" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Evaluation of the Resilience of Real Estate and Property Stocks to Inflation and Interest Rate Uncertainty: Implementation of Two Asset Pricing Models" data-journal="jrfm"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1911-8074/17/12/530">Evaluation of the Resilience of Real Estate and Property Stocks to Inflation and Interest Rate Uncertainty: Implementation of Two Asset Pricing Models</a> <div class="authors"> by <span class="inlineblock "><strong>Nurdina Nurdina</strong>, </span><span class="inlineblock "><strong>Nurkholis Nurkholis</strong>, </span><span class="inlineblock "><strong>Noval Adib</strong> and </span><span class="inlineblock "><strong>Sari Atmini</strong></span> </div> <div class="color-grey-dark"> <em>J. Risk Financial Manag.</em> <b>2024</b>, <em>17</em>(12), 530; <a href="https://doi.org/10.3390/jrfm17120530">https://doi.org/10.3390/jrfm17120530</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Property stocks are an attractive alternative investment for investors who want passive income. Investors’ decisions focus not only on maximizing returns but also on reducing risk. This study examines the extent to which macroeconomic factors affect stock performance by comparing the effectiveness of <a href="#" data-counterslink = "https://www.mdpi.com/1911-8074/17/12/530/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Property stocks are an attractive alternative investment for investors who want passive income. Investors’ decisions focus not only on maximizing returns but also on reducing risk. This study examines the extent to which macroeconomic factors affect stock performance by comparing the effectiveness of the Fama–French five-factor model (5FF) and Fama–French seven-factor model (7FF) in estimating returns. This study also verifies Fisher’s theory in the context of property and real estate stocks. The research data used are property and real estate stocks in the Indonesian capital market. The data are processed using the OLS estimation method, and Akaike’s Information Criterion (AIC) is used to choose the optimal model. The results show that property and real estate stocks in Indonesia with negative profitability at all quantiles can hedge inflation and interest rates. However, the interest rates are not the only factor affecting the market risk. The 7FF model is better at explaining the variability of stock portfolio returns. This research makes an essential contribution to the financial literature in Indonesia, particularly in the context of portfolio management in the property and real estate sector. <a href="/1911-8074/17/12/530">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/jrfm/special_issues/M1623X9673 ">Advances in Macroeconomics and Financial Markets</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1526904" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 22 pages, 3675 KiB   </span> <a href="/1996-1073/17/23/5852/pdf?version=1732268004" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Dynamic Anomaly Detection in the Chinese Energy Market During Financial Turbulence Using Ratio Mutual Information and Crude Oil Price Movements" data-journal="energies"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1996-1073/17/23/5852">Dynamic Anomaly Detection in the Chinese Energy Market During Financial Turbulence Using Ratio Mutual Information and Crude Oil Price Movements</a> <div class="authors"> by <span class="inlineblock "><strong>Lin Xiao</strong> and </span><span class="inlineblock "><strong>Arash Sioofy Khoojine</strong></span> </div> <div class="color-grey-dark"> <em>Energies</em> <b>2024</b>, <em>17</em>(23), 5852; <a href="https://doi.org/10.3390/en17235852">https://doi.org/10.3390/en17235852</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Investigating the stability of and fluctuations in the energy market has long been of interest to researchers and financial market participants. This study aimed to analyze the Chinese energy market, focusing on its volatility and response to financial tensions. For this purpose, data <a href="#" data-counterslink = "https://www.mdpi.com/1996-1073/17/23/5852/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Investigating the stability of and fluctuations in the energy market has long been of interest to researchers and financial market participants. This study aimed to analyze the Chinese energy market, focusing on its volatility and response to financial tensions. For this purpose, data from eight major financial companies, which were selected based on their market share in Shanghai’s and Shenzhen’s financial markets, were collected from January 2014 to December 2023. In this study, stock prices and trading volumes were used as the key variables to build bootstrap-based minimum spanning trees (BMSTs) using ratio mutual information (RMI). Then, using the sliding window procedure, the major network characteristics were derived to create an anomaly-detection tool using the multivariate exponentially weighted moving average (MEWMA), along with the Brent crude oil price index as a benchmark and a global oil price indicator. This framework’s stability was evaluated through stress testing with five scenarios designed for this purpose. The results demonstrate that during periods of high oil price volatility, such as during the turbulence in the stock market in 2015 and the COVID-19 pandemic in 2020, the network topologies became more centralized, which shows that the market’s instability increased. This framework successfully identifies anomalies and proves to be a valuable tool for market players and policymakers in evaluating companies that are active in the energy sector and predicting possible instabilities, which could be useful in monitoring financial markets and improving decision-making processes in the energy sector. In addition, the integration of other macroeconomic factors into this field could strengthen the identification of anomalies and be considered a field for possible research. <a href="/1996-1073/17/23/5852">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/energies/sections/energy_economics_policy">C: Energy Economics and Policy</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1996-1073/17/23/5852/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526904"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526904"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526904" data-cycle-prev="#prev1526904" data-cycle-progressive="#images1526904" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526904-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g001-550.jpg?1732268199" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526904" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g002-550.jpg?1732268200'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g003-550.jpg?1732268201'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g004-550.jpg?1732268203'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g005-550.jpg?1732268209'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g006-550.jpg?1732268211'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g007-550.jpg?1732268213'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g008-550.jpg?1732268214'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g009-550.jpg?1732268216'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1526904-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g010-550.jpg?1732268217'><p>Figure 10</p></div></script></div></div><div id="article-1526904-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g001-550.jpg?1732268199" title=" <strong>Figure 1</strong><br/> <p>Time series of stock prices and the traded volumes of the eight energy-related companies in the Chinese stock market from 2014 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g002-550.jpg?1732268200" title=" <strong>Figure 2</strong><br/> <p>Price鈥搗olume ratios of the eight selected companies from 2014 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g003-550.jpg?1732268201" title=" <strong>Figure 3</strong><br/> <p>Stock returns and traded volumes for the eight companies from 2014 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g004-550.jpg?1732268203" title=" <strong>Figure 4</strong><br/> <p>Fluctuations in the <math display="inline"><semantics> <msub> <mi>d</mi> <mn>1</mn> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>d</mi> <mn>2</mn> </msub> </semantics></math>, and <math display="inline"><semantics> <msub> <mi>d</mi> <mn>3</mn> </msub> </semantics></math> norms in stock prices and volumes of the eight selected energy companies from 2014 to 2023.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g005-550.jpg?1732268209" title=" <strong>Figure 5</strong><br/> <p>Bar plot illustrating the network characteristics鈥攏ode degree, node strength, eigenvalue centrality, and closeness centrality鈥攐f the BMSTs constructed from the critical windows.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g006-550.jpg?1732268211" title=" <strong>Figure 6</strong><br/> <p>Bar plot illustrating the communicability scores of the BMSTs constructed from the five critical windows: 29, 59, 850, 880, and 953.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g007-550.jpg?1732268213" title=" <strong>Figure 7</strong><br/> <p>Bootstrapped-based Minimum Spanning Trees of the critical Windows 29, 59, 850, 880, and 953, with reliability scores as edge weights.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g008-550.jpg?1732268214" title=" <strong>Figure 8</strong><br/> <p>Circular layout of the bootstrapped-based minimum spanning trees: pre-turbulence, turbulence, and post-turbulence in windows 28, 29, and 30.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g009-550.jpg?1732268216" title=" <strong>Figure 9</strong><br/> <p>Movement of Brent crude oil price from 2014 to 2023 with the critical periods highlighted.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05852/article_deploy/html/images/energies-17-05852-g010-550.jpg?1732268217" title=" <strong>Figure 10</strong><br/> <p>The MEWMA statistic over the period of time for Window 29 with its upper and lower control limits shown as dashed lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/23/5852'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1526281" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 423 KiB   </span> <a href="/2078-2489/15/12/743/pdf?version=1732264108" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Implicit-Causality-Exploration-Enabled Graph Neural Network for Stock Prediction" data-journal="information"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2078-2489/15/12/743">Implicit-Causality-Exploration-Enabled Graph Neural Network for Stock Prediction</a> <div class="authors"> by <span class="inlineblock "><strong>Ying Li</strong>, </span><span class="inlineblock "><strong>Xiaosha Xue</strong>, </span><span class="inlineblock "><strong>Zhipeng Liu</strong>, </span><span class="inlineblock "><strong>Peibo Duan</strong> and </span><span class="inlineblock "><strong>Bin Zhang</strong></span> </div> <div class="color-grey-dark"> <em>Information</em> <b>2024</b>, <em>15</em>(12), 743; <a href="https://doi.org/10.3390/info15120743">https://doi.org/10.3390/info15120743</a> - 21 Nov 2024 </div> Viewed by 185 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Accurate stock prediction plays an important role in financial markets and can aid investors in making well-informed decisions and optimizing their investment strategies. Relationships exist among stocks in the market, leading to high correlation in their prices. Recently, several methods have been proposed <a href="#" data-counterslink = "https://www.mdpi.com/2078-2489/15/12/743/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Accurate stock prediction plays an important role in financial markets and can aid investors in making well-informed decisions and optimizing their investment strategies. Relationships exist among stocks in the market, leading to high correlation in their prices. Recently, several methods have been proposed to mine such relationships in order to enhance forecasting results. However, previous works have focused on exploring the correlations among stocks while neglecting the causal characteristics, thereby restricting the predictive performance. Furthermore, due to the diversity of relationships, existing methods are unable to handle both dynamic and static relationships simultaneously. To address the limitations of prior research, we introduce a novel stock trend forecasting framework capable of mining the causal relationships that affect changes in companies’ stock prices and simultaneously extracts both dynamic and static features to enhance the forecasting performance. Extensive experimental results in the Chinese stock market demonstrate that the proposed framework achieves obvious improvement against multiple state-of-the-art approaches. <a href="/2078-2489/15/12/743">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2078-2489/15/12/743/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526281"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526281"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526281" data-cycle-prev="#prev1526281" data-cycle-progressive="#images1526281" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526281-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-ag-550.jpg?1732264207" alt="" style="border: 0;"><p>Graphical abstract</p></div><script id="images1526281" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526281-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-g001-550.jpg?1732264206'><p>Figure 1</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526281-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-g002-550.jpg?1732264207'><p>Figure 2</p></div></script></div></div><div id="article-1526281-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-ag-550.jpg?1732264207" title=" <strong>Graphical abstract</strong><br/><strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2078-2489/15/12/743'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-g001-550.jpg?1732264206" title=" <strong>Figure 1</strong><br/> <p>Two stocks with Granger causality have low correlation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2078-2489/15/12/743'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/information/information-15-00743/article_deploy/html/images/information-15-00743-g002-550.jpg?1732264207" title=" <strong>Figure 2</strong><br/> <p>The framework of DSF-GNN. DSF-GNN contains four steps: temporal feature representation (TFR), relational feature encoding (RFE), relational feature fusion (RFF), and prediction.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2078-2489/15/12/743'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1525931" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 43 pages, 4570 KiB   </span> <a href="/2076-3417/14/23/10782/pdf?version=1732181247" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/14/23/10782">Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews</a> <div class="authors"> by <span class="inlineblock "><strong>Miehleketo Mathebula</strong>, </span><span class="inlineblock "><strong>Abiodun Modupe</strong> and </span><span class="inlineblock "><strong>Vukosi Marivate</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2024</b>, <em>14</em>(23), 10782; <a href="https://doi.org/10.3390/app142310782">https://doi.org/10.3390/app142310782</a> - 21 Nov 2024 </div> Viewed by 262 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Sentiment analysis is a well-known task that has been used to analyse customer feedback reviews and media headlines to detect the sentimental personality or polarisation of a given text. With the growth of social media and other online platforms, like Twitter (now branded <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/14/23/10782/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Sentiment analysis is a well-known task that has been used to analyse customer feedback reviews and media headlines to detect the sentimental personality or polarisation of a given text. With the growth of social media and other online platforms, like Twitter (now branded as X), Facebook, blogs, and others, it has been used in the investment community to monitor customer feedback, reviews, and news headlines about financial institutions’ products and services to ensure business success and prioritise aspects of customer relationship management. Supervised learning algorithms have been popularly employed for this task, but the performance of these models has been compromised due to the brevity of the content and the presence of idiomatic expressions, sound imitations, and abbreviations. Additionally, the pre-training of a larger language model (PTLM) struggles to capture bidirectional contextual knowledge learnt through word dependency because the sentence-level representation fails to take broad features into account. We develop a novel structure called language feature extraction and adaptation for reviews (LFEAR), an advanced natural language model that amalgamates retrieval-augmented generation (RAG) with a conversation format for an auto-regressive fine-tuning model (ARFT). This helps to overcome the limitations of lexicon-based tools and the reliance on pre-defined sentiment lexicons, which may not fully capture the range of sentiments in natural language and address questions on various topics and tasks. LFEAR is fine-tuned on Hellopeter reviews that incorporate industry-specific contextual information retrieval to show resilience and flexibility for various tasks, including analysing sentiments in reviews of restaurants, movies, politics, and financial products. The proposed model achieved an average precision score of 98.45%, answer correctness of 93.85%, and context precision of 97.69% based on Retrieval-Augmented Generation Assessment (RAGAS) metrics. The LFEAR model is effective in conducting sentiment analysis across various domains due to its adaptability and scalable inference mechanism. It considers unique language characteristics and patterns in specific domains to ensure accurate sentiment annotation. This is particularly beneficial for individuals in the financial sector, such as investors and institutions, including those listed on the Johannesburg Stock Exchange (JSE), which is the primary stock exchange in South Africa and plays a significant role in the country’s financial market. Future initiatives will focus on incorporating a wider range of data sources and improving the system’s ability to express nuanced sentiments effectively, enhancing its usefulness in diverse real-world scenarios. <a href="/2076-3417/14/23/10782">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/WFXM2FW402 ">Applications of Data Science and Artificial Intelligence</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/14/23/10782/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1525931"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1525931"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1525931" data-cycle-prev="#prev1525931" data-cycle-progressive="#images1525931" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1525931-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g001-550.jpg?1732181328" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1525931" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g002-550.jpg?1732181328'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g003-550.jpg?1732181329'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g004-550.jpg?1732181330'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g005-550.jpg?1732181331'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g006-550.jpg?1732181333'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g007-550.jpg?1732181335'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g008-550.jpg?1732181337'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g009-550.jpg?1732181339'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g010-550.jpg?1732181342'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g011-550.jpg?1732181343'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g012-550.jpg?1732181345'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g013-550.jpg?1732181347'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1525931-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g014-550.jpg?1732181348'><p>Figure 14</p></div></script></div></div><div id="article-1525931-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g001-550.jpg?1732181328" title=" <strong>Figure 1</strong><br/> <p>Proposed LFEAR model for sentiment analysis.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g002-550.jpg?1732181328" title=" <strong>Figure 2</strong><br/> <p>Few-shot learning with the Meta-Llama-3 model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g003-550.jpg?1732181329" title=" <strong>Figure 3</strong><br/> <p>Chain-of-thought reasoning with the OpenAI GPT-4o Mini model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g004-550.jpg?1732181330" title=" <strong>Figure 4</strong><br/> <p>Reason and Act with OpenAI GPT-3.5 Turbo Model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g005-550.jpg?1732181331" title=" <strong>Figure 5</strong><br/> <p>Word clouds of frequently used terms in negative and positive Hellopeter reviews. (<b>a</b>) Negative; (<b>b</b>) Positive.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g006-550.jpg?1732181333" title=" <strong>Figure 6</strong><br/> <p>Distribution of sentiment polarity scores in Hellopeter reviews.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g007-550.jpg?1732181335" title=" <strong>Figure 7</strong><br/> <p>Scattertext visualisation of positive and negative words.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g008-550.jpg?1732181337" title=" <strong>Figure 8</strong><br/> <p>Confusion matrices for Llama models on the Hellopeter dataset. (<b>a</b>) Llama-2-7b-hf confusion matrix; (<b>b</b>) Meta-Llama-3-8B-Instruct confusion matrix.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g009-550.jpg?1732181339" title=" <strong>Figure 9</strong><br/> <p>Confusion matrices for GPT Models on the Hellopeter Dataset. (<b>a</b>) gpt-3.5-turbo-0125 confusion matrix; (<b>b</b>) gpt-4o-mini-2024-07-18 confusion matrix.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g010-550.jpg?1732181342" title=" <strong>Figure 10</strong><br/> <p>Confusion matrix for the proposed inference model on the Hellopeter dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g011-550.jpg?1732181343" title=" <strong>Figure 11</strong><br/> <p>RAGAS performance metrics for the proposed inference model on the Hellopeter dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g012-550.jpg?1732181345" title=" <strong>Figure 12</strong><br/> <p>LFEAR distribution of results.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g013-550.jpg?1732181347" title=" <strong>Figure 13</strong><br/> <p>Sentiment intensity analysis results for the Hellopeter dataset using LFEAR. (<b>a</b>) LFEAR Sentiment intensity distribution in the Hellopeter dataset; (<b>b</b>) LFEAR proportion of sentiment categories in the Hellopeter dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10782/article_deploy/html/images/applsci-14-10782-g014-550.jpg?1732181348" title=" <strong>Figure 14</strong><br/> <p>LFEAR performance on the Hellopeter dataset. (<b>a</b>) Polarity score distribution; (<b>b</b>) Vendi score distribution.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/23/10782'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1525552" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 24 pages, 7050 KiB   </span> <a href="/1996-1073/17/22/5806/pdf?version=1732172480" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Quantile Connectedness of Uncertainty Indices, Carbon Emissions, Energy, and Green Assets: Insights from Extreme Market Conditions" data-journal="energies"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1996-1073/17/22/5806">Quantile Connectedness of Uncertainty Indices, Carbon Emissions, Energy, and Green Assets: Insights from Extreme Market Conditions</a> <div class="authors"> by <span class="inlineblock "><strong>Tiantian Liu</strong>, </span><span class="inlineblock "><strong>Yulian Zhang</strong>, </span><span class="inlineblock "><strong>Wenting Zhang</strong> and </span><span class="inlineblock "><strong>Shigeyuki Hamori</strong></span> </div> <div class="color-grey-dark"> <em>Energies</em> <b>2024</b>, <em>17</em>(22), 5806; <a href="https://doi.org/10.3390/en17225806">https://doi.org/10.3390/en17225806</a> - 20 Nov 2024 </div> Viewed by 267 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In this study, we investigate the volatility spillover effects across uncertainty indices (Infectious Disease Equity Market Volatility Tracker (IDEMV) and Geopolitical Risk Index (GPR)), carbon emissions, crude oil, natural gas, and green assets (green bonds and green stock) under extreme market conditions based <a href="#" data-counterslink = "https://www.mdpi.com/1996-1073/17/22/5806/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In this study, we investigate the volatility spillover effects across uncertainty indices (Infectious Disease Equity Market Volatility Tracker (IDEMV) and Geopolitical Risk Index (GPR)), carbon emissions, crude oil, natural gas, and green assets (green bonds and green stock) under extreme market conditions based on the quantile connectedness approach. The empirical findings reveal that the total and directional connectedness across green assets and other variables in extreme market conditions is much higher than that in the median, and there is obvious asymmetry in the connectedness measured at the extreme lower and upper quantiles. Our findings suggest that the uncertainty caused by COVID-19 has a more significant impact on green assets than the uncertainty related to the Russia–Ukraine war under normal and extreme market conditions. Furthermore, we discover that the uncertainty indices are more important in predicting green asset volatility under extreme market conditions than they are in the normal market. Finally, we observe that the dynamic total spillover effects in the extreme quantiles are significantly higher than those in the median. <a href="/1996-1073/17/22/5806">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/energies/special_issues/YR0DXHQ0PF ">International Finance and Energy Markets: Energy Supplying, Prices, Investments and Trends</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1996-1073/17/22/5806/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1525552"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1525552"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1525552" data-cycle-prev="#prev1525552" data-cycle-progressive="#images1525552" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1525552-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g001-550.jpg?1732172580" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1525552" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g002-550.jpg?1732172581'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g003a-550.jpg?1732172583'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g003b-550.jpg?1732172584'><p>Figure 3 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g004-550.jpg?1732172587'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g005-550.jpg?1732172589'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g006a-550.jpg?1732172589'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g006b-550.jpg?1732172591'><p>Figure 6 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g007-550.jpg?1732172594'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g008a-550.jpg?1732172596'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g008b-550.jpg?1732172598'><p>Figure 8 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g009a-550.jpg?1732172599'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1525552-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g009b-550.jpg?1732172601'><p>Figure 9 Cont.</p></div></script></div></div><div id="article-1525552-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g001-550.jpg?1732172580" title=" <strong>Figure 1</strong><br/> <p>Time variations of variables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g002-550.jpg?1732172581" title=" <strong>Figure 2</strong><br/> <p>Volatility connectedness network plot at the median, lower, and upper quantiles. Note: The color of the nodes indicates whether they are net transmitters (red) or net receivers (green) of the system. The size of a node reflects the magnitude of its net connectedness. The edge arrow direction and edge thickness represent the direction and strength of the net pairwise connectedness between a pair of markets, respectively. GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g003a-550.jpg?1732172583" title=" <strong>Figure 3</strong><br/> <p>Total spillover effects at the median, lower, and upper quantiles. Note: The dynamic spillover effects were captured using a 200-day rolling window based on a QVAR model with a lag of 5 (BIC) and a 10-step-ahead forecast horizon.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g003b-550.jpg?1732172584" title=" <strong>Figure 3 Cont.</strong><br/> <p>Total spillover effects at the median, lower, and upper quantiles. Note: The dynamic spillover effects were captured using a 200-day rolling window based on a QVAR model with a lag of 5 (BIC) and a 10-step-ahead forecast horizon.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g004-550.jpg?1732172587" title=" <strong>Figure 4</strong><br/> <p>Net directional spillover effects at the median. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g005-550.jpg?1732172589" title=" <strong>Figure 5</strong><br/> <p>Net directional spillover effects at the lower quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g006a-550.jpg?1732172589" title=" <strong>Figure 6</strong><br/> <p>Net directional spillover effects at the upper quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g006b-550.jpg?1732172591" title=" <strong>Figure 6 Cont.</strong><br/> <p>Net directional spillover effects at the upper quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g007-550.jpg?1732172594" title=" <strong>Figure 7</strong><br/> <p>Net pairwise directional spillover effects between green assets and other assets at the median. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g008a-550.jpg?1732172596" title=" <strong>Figure 8</strong><br/> <p>Net pairwise directional spillover effects between green assets and other assets at the lower quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g008b-550.jpg?1732172598" title=" <strong>Figure 8 Cont.</strong><br/> <p>Net pairwise directional spillover effects between green assets and other assets at the lower quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g009a-550.jpg?1732172599" title=" <strong>Figure 9</strong><br/> <p>Net pairwise directional spillover effects between green assets and other assets at the upper quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05806/article_deploy/html/images/energies-17-05806-g009b-550.jpg?1732172601" title=" <strong>Figure 9 Cont.</strong><br/> <p>Net pairwise directional spillover effects between green assets and other assets at the upper quantile. Note: GB, Solactive Green Bond Index; GS, Standard &amp; Poor Global Clean Energy Index; Oil, Brent Crude Oil; Gas, Henry Hub Natural Gas; Carbon, Carbon Emissions Futures; IDEMV, Infectious Disease Equity Market Volatility Tracker; GPR, Geopolitical Risk Index.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/22/5806'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1524898" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 20 pages, 305 KiB   </span> <a href="/2075-5309/14/11/3690/pdf?version=1732092998" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Impact of Short-Term Rentals on Long-Term Rentals and the Housing Market in Riyadh" data-journal="buildings"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2075-5309/14/11/3690">The Impact of Short-Term Rentals on Long-Term Rentals and the Housing Market in Riyadh</a> <div class="authors"> by <span class="inlineblock "><strong>Tahar Ledraa</strong> and </span><span class="inlineblock "><strong>Sameeh Alarabi</strong></span> </div> <div class="color-grey-dark"> <em>Buildings</em> <b>2024</b>, <em>14</em>(11), 3690; <a href="https://doi.org/10.3390/buildings14113690">https://doi.org/10.3390/buildings14113690</a> - 20 Nov 2024 </div> Viewed by 280 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Riyadh has recently witnessed rapid growth in the use of short-term rentals. Their impact on the city’s housing market and long-term rentals has been critical. The emergence of recreational festivals such as the Riyadh and Diriyah Seasons, with their accompanying events, as well <a href="#" data-counterslink = "https://www.mdpi.com/2075-5309/14/11/3690/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Riyadh has recently witnessed rapid growth in the use of short-term rentals. Their impact on the city’s housing market and long-term rentals has been critical. The emergence of recreational festivals such as the Riyadh and Diriyah Seasons, with their accompanying events, as well as the widespread use of daily rental platforms such as Airbnb, have created a new market for short-term rentals that has changed the city’s rental landscape. This study compared data on the number of units geared toward daily rent and their average daily rates (ADRs), obtained from the Airbnb platform, with data on long-term rental units and their revenue, extracted from the Ejar platform. The data cover the five sectors of Riyadh city. Sample neighborhoods were selected from each sector. The results show that after a period of stagnation due to the precautionary measures taken during the COVID-19 pandemic, the short-term rental market saw a significant recovery once these measures were lifted. The emergence of the short-term rental market has negatively affected the long-term rental market by drying up its stock and raising rent prices, thus leading to tourism-induced displacement of low-income residents and further exacerbating the housing problem in the city. Therefore, there is an urgent need to regulate this new rental market to maintain a balance between short- and long-term markets in Riyadh. <a href="/2075-5309/14/11/3690">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/buildings/sections/Architectural_Design">Architectural Design, Urban Science, and Real Estate</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1524593" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 1068 KiB   </span> <a href="/2571-9394/6/4/53/pdf?version=1732095368" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Constructing Cybersecurity Stocks Portfolio Using AI" data-journal="forecasting"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2571-9394/6/4/53">Constructing Cybersecurity Stocks Portfolio Using AI</a> <div class="authors"> by <span class="inlineblock "><strong>Avishay Aiche</strong>, </span><span class="inlineblock "><strong>Zvi Winer</strong> and </span><span class="inlineblock "><strong>Gil Cohen</strong></span> </div> <div class="color-grey-dark"> <em>Forecasting</em> <b>2024</b>, <em>6</em>(4), 1065-1077; <a href="https://doi.org/10.3390/forecast6040053">https://doi.org/10.3390/forecast6040053</a> - 19 Nov 2024 </div> Viewed by 175 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> This study explores the application of artificial intelligence, specifically ChatGPT-4o, in constructing and managing a portfolio of cybersecurity stocks over the period from Q1 2018 to Q1 2024. Leveraging advanced machine learning models, fundamental analysis, sentiment analysis, and optimization techniques, the AI-driven portfolio <a href="#" data-counterslink = "https://www.mdpi.com/2571-9394/6/4/53/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> This study explores the application of artificial intelligence, specifically ChatGPT-4o, in constructing and managing a portfolio of cybersecurity stocks over the period from Q1 2018 to Q1 2024. Leveraging advanced machine learning models, fundamental analysis, sentiment analysis, and optimization techniques, the AI-driven portfolio significantly outperformed leading cybersecurity ETFs, as well as broader market indices such as the Nasdaq 100 (QQQ) and S&P 500 (SPY). The methodology employed included data collection, stock filtering, predictive modeling using Random Forests and Support Vector Machines (SVMs), sentiment analysis through natural language processing (NLP), and portfolio optimization using Mean-Variance Optimization (MVO), with quarterly rebalancing to ensure responsiveness to evolving market conditions. The AI-selected portfolio achieved a total return of 273%, with strong risk-adjusted performance as demonstrated by key metrics such as the Sharpe ratio, highlighting the effectiveness of an AI-based approach in navigating market complexities and generating superior returns. The results of this study indicate that AI-driven portfolio management can uncover investment opportunities that traditional methods may overlook, offering a competitive edge in the cybersecurity sector and promising enhanced predictive accuracy, efficiency, and overall investment success as AI technologies continue to evolve. <a href="/2571-9394/6/4/53">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2571-9394/6/4/53/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1524593"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1524593"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1524593" data-cycle-prev="#prev1524593" data-cycle-progressive="#images1524593" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1524593-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g001-550.jpg?1732095441" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1524593" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1524593-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g002-550.jpg?1732095442'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1524593-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g003-550.jpg?1732095443'><p>Figure 3</p></div></script></div></div><div id="article-1524593-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g001-550.jpg?1732095441" title=" <strong>Figure 1</strong><br/> <p>Cumulative profit over time from Q1 2018 to Q1 2024, demonstrating the significant upward trend and overall growth in the portfolio鈥檚 value, with notable spikes and recoveries reflecting market dynamics and strategic stock selections.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2571-9394/6/4/53'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g002-550.jpg?1732095442" title=" <strong>Figure 2</strong><br/> <p>Portfolio value over time from Q1 2018 to Q1 2024, highlighting the consistent growth trajectory, periodic market corrections, and the portfolio鈥檚 ability to recover and sustain value, peaking at Q1 2024.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2571-9394/6/4/53'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/forecasting/forecasting-06-00053/article_deploy/html/images/forecasting-06-00053-g003-550.jpg?1732095443" title=" <strong>Figure 3</strong><br/> <p>Quarterly profit over time from Q1 2018 to Q1 2024, showing variability in quarterly profits with substantial gains and occasional losses, reflecting the dynamic nature of the cybersecurity sector and strategic stock performance.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2571-9394/6/4/53'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1524080" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 4654 KiB   </span> <a href="/2079-8954/12/11/503/pdf?version=1732066532" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="System Dynamics Modeling: Technological Solution to Evaluating Cold-Chain Meat Packaging Scenarios" data-journal="systems"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-8954/12/11/503">System Dynamics Modeling: Technological Solution to Evaluating Cold-Chain Meat Packaging Scenarios</a> <div class="authors"> by <span class="inlineblock "><strong>Ernesto A. Lagarda-Leyva</strong>, </span><span class="inlineblock "><strong>Luis E. Hern谩ndez-Valdez</strong> and </span><span class="inlineblock "><strong>Alfredo Bueno-Solano</strong></span> </div> <div class="color-grey-dark"> <em>Systems</em> <b>2024</b>, <em>12</em>(11), 503; <a href="https://doi.org/10.3390/systems12110503">https://doi.org/10.3390/systems12110503</a> - 19 Nov 2024 </div> Viewed by 425 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> A cold-chain meat packaging project was developed for a meat product company in northwestern Mexico that moves high volumes of fresh meat into national and international markets. The objective of the present research is to evaluate the supply process for three types of <a href="#" data-counterslink = "https://www.mdpi.com/2079-8954/12/11/503/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> A cold-chain meat packaging project was developed for a meat product company in northwestern Mexico that moves high volumes of fresh meat into national and international markets. The objective of the present research is to evaluate the supply process for three types of thermo-shrinkable polyethylene bags to provide a technological solution for high-volume meat packaging based on a graphical user interface. A system dynamics (SD) methodology is developed in seven stages to generate a technological solution: (1) system mapping; (2) causal diagram construction; (3) stock, flow modeling, and equations; (4) model simulation; (5) model validation; (6) scenarios and multicriteria analysis; and (7) graphical user interface development. The main result for the company was a technological solution that could communicate with decision-makers and the proposed graphical user interface. Future optimistic and pessimistic scenarios were self-evaluated based on the current situation related to three thermo-shrinkable bags used for selling high volumes of fresh meat. In these solutions, previously simulated costs and savings can be implemented in a real situation. Quantitative graphical user interface data can be observed to adequately manage box and bag inventories and minimize costs. Using SD enables the development of technological solutions in complex environments with robust simulations and models that offer data to people interested in the system under study. <a href="/2079-8954/12/11/503">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/systems/special_issues/J65ZM8UANS ">The Systems Thinking Approach to Strategic Management</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-8954/12/11/503/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1524080"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1524080"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1524080" data-cycle-prev="#prev1524080" data-cycle-progressive="#images1524080" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1524080-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g001-550.jpg?1732066701" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1524080" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g002-550.jpg?1732066702'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g003-550.jpg?1732066703'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g004-550.jpg?1732066705'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g005-550.jpg?1732066706'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g006-550.jpg?1732066708'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g007-550.jpg?1732066709'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g008-550.jpg?1732066710'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g009-550.jpg?1732066711'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g010-550.jpg?1732066713'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g011-550.jpg?1732066714'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g012-550.jpg?1732066718'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g013-550.jpg?1732066719'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g014-550.jpg?1732066720'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1524080-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g015-550.jpg?1732066721'><p>Figure 15</p></div></script></div></div><div id="article-1524080-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g001-550.jpg?1732066701" title=" <strong>Figure 1</strong><br/> <p>Cluster and supply chain map of meat product company. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g002-550.jpg?1732066702" title=" <strong>Figure 2</strong><br/> <p>Frequency of urgent purchase orders for thermo-shrinkable bags. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g003-550.jpg?1732066703" title=" <strong>Figure 3</strong><br/> <p>Procedure for developing graphical user interface with dynamic simulations. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g004-550.jpg?1732066705" title=" <strong>Figure 4</strong><br/> <p>Flow diagram of the process under study. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g005-550.jpg?1732066706" title=" <strong>Figure 5</strong><br/> <p>Causal diagram. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g006-550.jpg?1732066708" title=" <strong>Figure 6</strong><br/> <p>First stage for 16 脳 20 30 kg bags. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g007-550.jpg?1732066709" title=" <strong>Figure 7</strong><br/> <p>Packaging and distribution model for three types of clients. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g008-550.jpg?1732066710" title=" <strong>Figure 8</strong><br/> <p>Third stage. Investment in thermo-shrinkable 16 脳 20 bags. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g009-550.jpg?1732066711" title=" <strong>Figure 9</strong><br/> <p>Daily kilograms delivered in one month for the three types of clients (foreign clients 1 and 2 and local clients). Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g010-550.jpg?1732066713" title=" <strong>Figure 10</strong><br/> <p>Extreme proofing model. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g011-550.jpg?1732066714" title=" <strong>Figure 11</strong><br/> <p>Model validation comparing real data against simulated data for the 16 脳 20 thermo-shrinkable bags. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g012-550.jpg?1732066718" title=" <strong>Figure 12</strong><br/> <p>Background screen. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g013-550.jpg?1732066719" title=" <strong>Figure 13</strong><br/> <p>Bag graphics screen. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g014-550.jpg?1732066720" title=" <strong>Figure 14</strong><br/> <p>Box chart screen. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/systems/systems-12-00503/article_deploy/html/images/systems-12-00503-g015-550.jpg?1732066721" title=" <strong>Figure 15</strong><br/> <p>Investment data for 16 脳 20 bags and boxes. Source: Own production.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-8954/12/11/503'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1523173" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 4793 KiB   </span> <a href="/1911-8074/17/11/518/pdf?version=1731918254" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Oil Price Shocks and the Canadian Stock Market" data-journal="jrfm"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1911-8074/17/11/518">Oil Price Shocks and the Canadian Stock Market</a> <div class="authors"> by <span class="inlineblock "><strong>Ruiqi Tan</strong> and </span><span class="inlineblock "><strong>Wei Dai</strong></span> </div> <div class="color-grey-dark"> <em>J. Risk Financial Manag.</em> <b>2024</b>, <em>17</em>(11), 518; <a href="https://doi.org/10.3390/jrfm17110518">https://doi.org/10.3390/jrfm17110518</a> - 18 Nov 2024 </div> Viewed by 361 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In this paper, we use monthly data from 1992 to 2022 and a structural VAR model to investigate the effects of oil supply shocks, aggregate demand shocks, and oil-specific demand shocks in the global crude oil market on the Canadian stock market. Our <a href="#" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/518/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In this paper, we use monthly data from 1992 to 2022 and a structural VAR model to investigate the effects of oil supply shocks, aggregate demand shocks, and oil-specific demand shocks in the global crude oil market on the Canadian stock market. Our analysis reveals that these shocks affect the S&P/TSX Composite Index and various sector-specific indices in different ways. Specifically, the response of the Canadian market to oil-specific demand shocks diverges notably from the U.S. market, highlighting Canada’s unique position as an oil-exporting country. In the long run, oil price shocks account for over 10% of the variation in the composite index and as much as 35% in the Energy sector index. <a href="/1911-8074/17/11/518">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/jrfm/special_issues/6WOI883349 ">Advanced Studies in Empirical Macroeconomics and Finance</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/518/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1523173"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1523173"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1523173" data-cycle-prev="#prev1523173" data-cycle-progressive="#images1523173" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1523173-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g001-550.jpg?1731918338" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1523173" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g002-550.jpg?1731918339'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g003-550.jpg?1731918340'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g004-550.jpg?1731918340'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g005-550.jpg?1731918341'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g006-550.jpg?1731918342'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g007-550.jpg?1731918343'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g008-550.jpg?1731918343'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g009-550.jpg?1731918344'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g010-550.jpg?1731918345'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g011-550.jpg?1731918345'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g012-550.jpg?1731918346'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1523173-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g013-550.jpg?1731918347'><p>Figure 13</p></div></script></div></div><div id="article-1523173-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g001-550.jpg?1731918338" title=" <strong>Figure 1</strong><br/> <p>Oil Price and the Canadian stock market indices.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g002-550.jpg?1731918339" title=" <strong>Figure 2</strong><br/> <p>Responses of the S&amp;P/TSX Composite Index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g003-550.jpg?1731918340" title=" <strong>Figure 3</strong><br/> <p>Responses of the Communication Service index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g004-550.jpg?1731918340" title=" <strong>Figure 4</strong><br/> <p>Responses of the Consumer Discretionary index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g005-550.jpg?1731918341" title=" <strong>Figure 5</strong><br/> <p>Responses of the Consumer Staples index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g006-550.jpg?1731918342" title=" <strong>Figure 6</strong><br/> <p>Responses of the Energy index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g007-550.jpg?1731918343" title=" <strong>Figure 7</strong><br/> <p>Responses of the Financials index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g008-550.jpg?1731918343" title=" <strong>Figure 8</strong><br/> <p>Responses of the Health Care index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g009-550.jpg?1731918344" title=" <strong>Figure 9</strong><br/> <p>Responses of the Industrials index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g010-550.jpg?1731918345" title=" <strong>Figure 10</strong><br/> <p>Responses of the Information Technology index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g011-550.jpg?1731918345" title=" <strong>Figure 11</strong><br/> <p>Responses of the Materials index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g012-550.jpg?1731918346" title=" <strong>Figure 12</strong><br/> <p>Responses of the Public Utilities index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00518/article_deploy/html/images/jrfm-17-00518-g013-550.jpg?1731918347" title=" <strong>Figure 13</strong><br/> <p>Responses of the Real Estate index to three structural shocks. Point estimates are indicated by solid red lines, with one-standard-error and two-standard-error bands represented by dashed and dotted lines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/518'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1523125" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 1925 KiB   </span> <a href="/1911-8074/17/11/517/pdf?version=1731915949" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Relationship Between ESG Scores and Value-at-Risk: A Vine Copula鈥揋ARCH Based Approach" data-journal="jrfm"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1911-8074/17/11/517">The Relationship Between ESG Scores and Value-at-Risk: A Vine Copula–GARCH Based Approach</a> <div class="authors"> by <span class="inlineblock "><strong>Stefano Demartis</strong> and </span><span class="inlineblock "><strong>Barbara Rogo</strong></span> </div> <div class="color-grey-dark"> <em>J. Risk Financial Manag.</em> <b>2024</b>, <em>17</em>(11), 517; <a href="https://doi.org/10.3390/jrfm17110517">https://doi.org/10.3390/jrfm17110517</a> - 18 Nov 2024 </div> Viewed by 301 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Recently, the introduction of Environmental, Social, and Governance (ESG) scores has become crucial for investment decisions and in minimizing portfolio risk. This study aims to understand the relationship between ESG scores and Value-at-Risk (VaR), computed by using a Vine copula–GARCH based approach, chosen <a href="#" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/517/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Recently, the introduction of Environmental, Social, and Governance (ESG) scores has become crucial for investment decisions and in minimizing portfolio risk. This study aims to understand the relationship between ESG scores and Value-at-Risk (VaR), computed by using a Vine copula–GARCH based approach, chosen for its reliability in detecting interdependencies among multiple stocks. In fact, one of the main challenges in estimating VaR for a stock portfolio is capturing the dependence structure among a large number of assets. The dataset consists of 16 companies listed on the FTSE100 index. The corresponding ESG scores were collected over a comprehensive period of five years, from 2018 to 2022, covering both normal and stressed market conditions. Additionally, a focused analysis was conducted for the period from 2020 to 2022 to isolate the specific effects of the COVID crisis. The results indicate that an increase in assets with the highest ESG scores reduces potential losses in the portfolio. This finding underscores the importance of integrating high-level ESG scores into portfolios to mitigate market risk. Additionally, during periods characterized by stressed market conditions, the impact of ESG scores on VaR is even more pronounced, demonstrating that sustainable assets are more resilient in times of crisis. <a href="/1911-8074/17/11/517">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/jrfm/sections/mathematics_finance">Mathematics and Finance</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/517/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1523125"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1523125"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1523125" data-cycle-prev="#prev1523125" data-cycle-progressive="#images1523125" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1523125-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g001-550.jpg?1731916143" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1523125" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1523125-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g002-550.jpg?1731916146'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1523125-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g003-550.jpg?1731916149'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1523125-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g004-550.jpg?1731916151'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1523125-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g005-550.jpg?1731916152'><p>Figure 5</p></div></script></div></div><div id="article-1523125-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g001-550.jpg?1731916143" title=" <strong>Figure 1</strong><br/> <p>Example of C-Vine structures for <math display="inline"><semantics> <mrow> <mi>d</mi> <mo>=</mo> <mn>4</mn> </mrow> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/517'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g002-550.jpg?1731916146" title=" <strong>Figure 2</strong><br/> <p>Daily log-returns.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/517'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g003-550.jpg?1731916149" title=" <strong>Figure 3</strong><br/> <p>Pairwise normalized contour plots. The value 0.71, highlighted and enlarged, represents the highest correlation among the analyzed pairs, observed between Shell (SHEL) and BP plc (BP).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/517'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g004-550.jpg?1731916151" title=" <strong>Figure 4</strong><br/> <p>The first tree structure of estimated R-Vine and Kendall鈥檚 tau values for each connected pair of stocks.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/517'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00517/article_deploy/html/images/jrfm-17-00517-g005-550.jpg?1731916152" title=" <strong>Figure 5</strong><br/> <p>The second tree structure of estimated R-Vine and Kendall鈥檚 tau values for each connected pair of stocks.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/517'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1523122" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 238 KiB   </span> <a href="/2076-3387/14/11/304/pdf?version=1731915731" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="How Much Does the CEO鈥檚 Age Impact Corporate Performance Under a Changing Environment?" data-journal="admsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3387/14/11/304">How Much Does the CEO’s Age Impact Corporate Performance Under a Changing Environment?</a> <div class="authors"> by <span class="inlineblock "><strong>Joohee Han</strong> and </span><span class="inlineblock "><strong>Sung Jun Jo</strong></span> </div> <div class="color-grey-dark"> <em>Adm. Sci.</em> <b>2024</b>, <em>14</em>(11), 304; <a href="https://doi.org/10.3390/admsci14110304">https://doi.org/10.3390/admsci14110304</a> - 18 Nov 2024 </div> Viewed by 305 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The recent technological innovations and the consequences of the pandemic are rapidly changing the management paradigm. Organizations that seek to survive and remain competitive must adapt to these changes. One strategy to cope with these environmental changes is to hire a younger CEO. <a href="#" data-counterslink = "https://www.mdpi.com/2076-3387/14/11/304/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The recent technological innovations and the consequences of the pandemic are rapidly changing the management paradigm. Organizations that seek to survive and remain competitive must adapt to these changes. One strategy to cope with these environmental changes is to hire a younger CEO. This study aims to empirically analyze how the age of the CEO affects the performance of the firm based on upper echelons theory. Using a sample of 706 CEOs of companies listed on the South Korean public stock market (KOSPI) as of 2023, we found that CEO age is positively related to financial performance. We also found that CEO age is negatively related to risk-taking behavior and innovation. These findings have both practical and theoretical implications, suggesting that the recent shift to the relationship between a long-term perspective and innovation have positive implications. Young CEOs often seek these perspectives and are more willing to be aggressive in investment and risk-taking behaviors in the interests offor an innovative business. <a href="/2076-3387/14/11/304">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/admsci/sections/strategic_management">Strategic Management</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1522473" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 256 KiB   </span> <a href="/1911-8074/17/11/514/pdf?version=1731750081" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Unveiling the Brew: Probing the Lingering Impact of the Luckin Coffee Scandal on the Liquidity of Chinese Cross-Listed Stocks" data-journal="jrfm"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1911-8074/17/11/514">Unveiling the Brew: Probing the Lingering Impact of the Luckin Coffee Scandal on the Liquidity of Chinese Cross-Listed Stocks</a> <div class="authors"> by <span class="inlineblock "><strong>Lee Kersting</strong>, </span><span class="inlineblock "><strong>Jang-Chul Kim</strong>, </span><span class="inlineblock "><strong>Sharif Mazumder</strong> and </span><span class="inlineblock "><strong>Qing Su</strong></span> </div> <div class="color-grey-dark"> <em>J. Risk Financial Manag.</em> <b>2024</b>, <em>17</em>(11), 514; <a href="https://doi.org/10.3390/jrfm17110514">https://doi.org/10.3390/jrfm17110514</a> - 16 Nov 2024 </div> Viewed by 475 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> This paper investigates the impact of the Luckin Coffee accounting scandal on stock liquidity and spillover effects in the financial market, focusing on Chinese companies listed on U.S. exchanges. Utilizing event studies, we analyze eight pivotal events related to the scandal to examine <a href="#" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/514/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> This paper investigates the impact of the Luckin Coffee accounting scandal on stock liquidity and spillover effects in the financial market, focusing on Chinese companies listed on U.S. exchanges. Utilizing event studies, we analyze eight pivotal events related to the scandal to examine stock liquidity and market quality changes. The results show a significant decline in Luckin’s stock liquidity during the scandal, while spillover effects on other Chinese stocks are limited. Comparisons with the Satyam accounting scandal suggest that individual company scandals may not substantially affect the liquidity of other stocks from the same country. The findings highlight the importance of robust regulatory frameworks and investor due diligence in safeguarding market integrity and restoring investor confidence. <a href="/1911-8074/17/11/514">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/jrfm/special_issues/7EVTR9213R ">Liquidity and Asset Pricing</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1522030" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 37 pages, 4052 KiB   </span> <a href="/2227-7099/12/11/309/pdf?version=1732077383" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Should South Asian Stock Market Investors Think Globally? Investigating Safe Haven Properties and Hedging Effectiveness" data-journal="economies"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2227-7099/12/11/309">Should South Asian Stock Market Investors Think Globally? Investigating Safe Haven Properties and Hedging Effectiveness</a> <div class="authors"> by <span class="inlineblock "><strong>Md. Abu Issa Gazi</strong>, </span><span class="inlineblock "><strong>Md. Nahiduzzaman</strong>, </span><span class="inlineblock "><strong>Sanjoy Kumar Sarker</strong>, </span><span class="inlineblock "><strong>Mohammad Bin Amin</strong>, </span><span class="inlineblock "><strong>Md. Ahsan Kabir</strong>, </span><span class="inlineblock "><strong>Fadoua Kouki</strong>, </span><span class="inlineblock "><strong>Abdul Rahman bin S Senathirajah</strong> and </span><span class="inlineblock "><strong>L谩szl贸 Erdey</strong></span> </div> <div class="color-grey-dark"> <em>Economies</em> <b>2024</b>, <em>12</em>(11), 309; <a href="https://doi.org/10.3390/economies12110309">https://doi.org/10.3390/economies12110309</a> - 15 Nov 2024 </div> Viewed by 689 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In this study, we examine the critical question of whether global equity and bond assets (both green and non-green) offer effective hedging and safe haven properties against stock market risks in South Asia, with a focus on Bangladesh, India, Pakistan, and Sri Lanka. <a href="#" data-counterslink = "https://www.mdpi.com/2227-7099/12/11/309/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In this study, we examine the critical question of whether global equity and bond assets (both green and non-green) offer effective hedging and safe haven properties against stock market risks in South Asia, with a focus on Bangladesh, India, Pakistan, and Sri Lanka. The increasing integration of global financial markets and the volatility experienced during recent economic crises raise important questions regarding the resilience of South Asian markets and the potential protective role of global assets. Drawing on methods like VaR and CVaR tail risk estimators, the DCC-GJR-GARCH time-varying connectedness approach, and cost-effectiveness tools for hedging, we analyze data spanning from 2014 to 2022 to assess these relationships comprehensively. Our findings demonstrate that stock markets in Bangladesh experience lower levels of downside risk in each quantile; however, safe haven properties from the global financial markets are effective for Bangladeshi, Indian, and Pakistani stock markets during the crisis period. Meanwhile, the Sri Lankan stock market neither receives hedging usefulness nor safe haven benefits from the same marketplaces. Additionally, global green assets, specifically green bond assets, are more reliable sources to ensure the safest investment for South Asian investors. Finally, the portfolio implications suggest that while traditional global equity assets offer ideal portfolio weights for South Asian investors, global equity and bond assets (both green and non-green) are the cheapest hedgers for equity investors, particularly in the Bangladeshi, Pakistani, and Sri Lankan stock markets. Moreover, these results hold significant implications for investors seeking to optimize portfolios and manage risk, as well as for policymakers aiming to strengthen regional market resilience. By clarifying the protective capacities of global assets, particularly green ones, our study contributes to a nuanced understanding of portfolio diversification and financial stability strategies within emerging markets in South Asia. <a href="/2227-7099/12/11/309">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2227-7099/12/11/309/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1522030"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1522030"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1522030" data-cycle-prev="#prev1522030" data-cycle-progressive="#images1522030" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1522030-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g001-550.jpg?1732077517" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1522030" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g002a-550.jpg?1732077519'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g002b-550.jpg?1732077522'><p>Figure 2 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g003-550.jpg?1732077524'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g004-550.jpg?1732077527'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g005-550.jpg?1732077529'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1522030-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g006-550.jpg?1732077532'><p>Figure 6</p></div></script></div></div><div id="article-1522030-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g001-550.jpg?1732077517" title=" <strong>Figure 1</strong><br/> <p>Price dynamic graph of each index [Notes: The vertical axis of the graph represents price, while the horizontal axis denotes the time period].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g002a-550.jpg?1732077519" title=" <strong>Figure 2</strong><br/> <p>Return dynamic graph of each index [Notes: The vertical axis of the graph represents return as percentage, while the horizontal axis denotes the time period].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g002b-550.jpg?1732077522" title=" <strong>Figure 2 Cont.</strong><br/> <p>Return dynamic graph of each index [Notes: The vertical axis of the graph represents return as percentage, while the horizontal axis denotes the time period].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g003-550.jpg?1732077524" title=" <strong>Figure 3</strong><br/> <p>Dynamic conditional correlation plots between global financial markets and the stock market of Bangladesh.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g004-550.jpg?1732077527" title=" <strong>Figure 4</strong><br/> <p>Dynamic conditional correlation plots between global financial markets and the stock market of India.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g005-550.jpg?1732077529" title=" <strong>Figure 5</strong><br/> <p>Dynamic conditional correlation plots between global financial markets and the stock market of Pakistan.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/economies/economies-12-00309/article_deploy/html/images/economies-12-00309-g006-550.jpg?1732077532" title=" <strong>Figure 6</strong><br/> <p>Dynamic conditional correlation plots between global financial markets and the stock market of Sri Lanka.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7099/12/11/309'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1521547" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 35 pages, 766 KiB   </span> <a href="/1911-8074/17/11/511/pdf?version=1731661264" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="IPO Pricing in Germany and Switzerland in the New Millennium: Tests on Underpricing and Long-Term Performance" data-journal="jrfm"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1911-8074/17/11/511">IPO Pricing in Germany and Switzerland in the New Millennium: Tests on Underpricing and Long-Term Performance</a> <div class="authors"> by <span class="inlineblock "><strong>Rohat Barihas</strong>, </span><span class="inlineblock "><strong>Peter Weber</strong> and </span><span class="inlineblock "><strong>Heinz Zimmermann</strong></span> </div> <div class="color-grey-dark"> <em>J. Risk Financial Manag.</em> <b>2024</b>, <em>17</em>(11), 511; <a href="https://doi.org/10.3390/jrfm17110511">https://doi.org/10.3390/jrfm17110511</a> - 15 Nov 2024 </div> Viewed by 361 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> We provide an updated analysis of initial public offerings (IPOs) by Swiss and German companies after the turn of the millennium up to 2020. We compare the characteristics of initial pricing to those observed in prior studies, test conventional hypotheses about underpricing cross-sectionally, <a href="#" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/511/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> We provide an updated analysis of initial public offerings (IPOs) by Swiss and German companies after the turn of the millennium up to 2020. We compare the characteristics of initial pricing to those observed in prior studies, test conventional hypotheses about underpricing cross-sectionally, and analyze the long-run performance of IPO firms. Our sample included 72 IPOs in Switzerland and 307 IPOs in Germany. We found an average (median) underpricing of 13.27% (7.19%) for Swiss IPOs and an average (median) of 21.50% (3.7%) for German IPOs; the averages dropped to 6.45% and 5.82%, respectively, after excluding the hot-issue market in 2000. Among the cross-sectional explanations, interesting effects can be observed with respect to the bookbuilding width and transparency standard of the listed market segment, as well as the reputation of the underwriter and the value of the greenshoe option. We documented strong post-issue underperformance for holding periods up to 120 months, which were, however, only present in the Swiss sample for median, not mean, returns. <a href="/1911-8074/17/11/511">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/jrfm/sections/financial_markets">Financial Markets</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1911-8074/17/11/511/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1521547-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/jrfm/jrfm-17-00511/article_deploy/html/images/jrfm-17-00511-g001-550.jpg?1731661346" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1521547-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/jrfm/jrfm-17-00511/article_deploy/html/images/jrfm-17-00511-g001-550.jpg?1731661346" title=" <strong>Figure 1</strong><br/> <p>Long-run performance (BHAR) of IPO firms: Switzerland, from 2000 to 2020鈥攃omparison to earlier study. BHAR are buy-and-hold (cumulative) returns for successively increasing holding periods The figure displays mean BHAR from our Swiss sample, from 2000 to 2020 (blue line), with those of the study of <a href="#B15-jrfm-17-00511" class="html-bibr">Drobetz et al.</a> (<a href="#B15-jrfm-17-00511" class="html-bibr">2005</a>) from 1983 to 2000 (orange line). The latter study however excludes the best- and worst-performing IPOs; therefore, for enhancing comparability, the <span class="html-italic">mean</span> BHAR is replaced by the <span class="html-italic">median</span> BHARs of our sample (dotted line).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1911-8074/17/11/511'>Full article</a></strong> "></a></div> </div> </div> <span class="more" style="display: none;"></span> </div> <div class="row footer"> <div class="listing-select-options"> <div class="columns small-12"> <div class="select generic-item"> <a href="#" class="export-options-show export-element export-expanded"> Show export options <i class="material-icons">expand_more</i> </a> <a href="#" class="export-options-show export-element"> Show export options <i class="material-icons">expand_less</i> </a> </div> <div class="listing-export-options export-element"> <div class="export-element" style="margin-top: 10px; margin-bottom: 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