CINXE.COM

<!DOCTYPE html> <html lang="en" dir="ltr"> <head>  <script async src="https://www.googletagmanager.com/gtag/js?id=G-P63WKM1TM1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-P63WKM1TM1'); </script>  <script type="text/javascript" > (function(m,e,t,r,i,k,a){m[i]=m[i]||function(){(m[i].a=m[i].a||[]).push(arguments)}; m[i].l=1*new Date(); for (var j = 0; j < document.scripts.length; j++) {if (document.scripts[j].src === r) { return; }} k=e.createElement(t),a=e.getElementsByTagName(t)[0],k.async=1,k.src=r,a.parentNode.insertBefore(k,a)}) (window, document, "script", "https://mc.yandex.ru/metrika/tag.js", "ym"); ym(55165297, "init", { clickmap:false, trackLinks:true, accurateTrackBounce:true, webvisor:false }); </script> <noscript><div><img src="https://mc.yandex.ru/watch/55165297" style="position:absolute; left:-9999px;" alt="" /></div></noscript>    <title>Search results for: stochastic volatility model</title> <meta name="description" content="Search results for: stochastic volatility model"> <meta name="keywords" content="stochastic volatility model"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="stochastic volatility model" name="q" aria-label="Search"> <button class="btn btn-light my-2 my-sm-0" type="submit"><i class="fas fa-search"></i></button> </form> </div> <div class="collapse navbar-collapse mt-1" id="navbarMenu"> <ul class="navbar-nav ml-auto align-items-center" id="mainNavMenu"> <li class="nav-item"> <a class="nav-link" href="https://waset.org/conferences" title="Conferences in 2024/2025/2026">Conferences</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/disciplines" title="Disciplines">Disciplines</a> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/committees" rel="nofollow">Committees</a> </li> <li class="nav-item dropdown"> <a class="nav-link dropdown-toggle" href="#" id="navbarDropdownPublications" role="button" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> Publications </a> <div class="dropdown-menu" aria-labelledby="navbarDropdownPublications"> <a class="dropdown-item" href="https://publications.waset.org/abstracts">Abstracts</a> <a class="dropdown-item" href="https://publications.waset.org">Periodicals</a> <a class="dropdown-item" href="https://publications.waset.org/archive">Archive</a> </div> </li> <li class="nav-item"> <a class="nav-link" href="https://waset.org/page/support" title="Support">Support</a> </li> </ul> </div> </div> </nav> </div> </header> <main> <div class="container mt-4"> <div class="row"> <div class="col-md-9 mx-auto"> <form method="get" action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="stochastic volatility model"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 17104</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: stochastic volatility model</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17104</span> Calibration of Hybrid Model and Arbitrage-Free Implied Volatility Surface</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kun%20Huang">Kun Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates whether the combination of local and stochastic volatility models can be calibrated exactly to any arbitrage-free implied volatility surface of European option. The risk neutral Brownian Bridge density is applied for calibration of the leverage function of our Hybrid model. Furthermore, the tails of marginal risk neutral density are generated by Generalized Extreme Value distribution in order to capture the properties of asset returns. The local volatility is generated from the arbitrage-free implied volatility surface using stochastic volatility inspired parameterization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=arbitrage%20free%20implied%20volatility" title="arbitrage free implied volatility">arbitrage free implied volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=calibration" title=" calibration"> calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20distribution" title=" extreme value distribution"> extreme value distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20model" title=" hybrid model"> hybrid model</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20volatility" title=" local volatility"> local volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=risk-neutral%20density" title=" risk-neutral density"> risk-neutral density</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility" title=" stochastic volatility"> stochastic volatility</a> </p> <a href="https://publications.waset.org/abstracts/62414/calibration-of-hybrid-model-and-arbitrage-free-implied-volatility-surface" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">267</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17103</span> Portfolio Optimization under a Hybrid Stochastic Volatility and Constant Elasticity of Variance Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jai%20Heui%20Kim">Jai Heui Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sotheara%20Veng"> Sotheara Veng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper studies the portfolio optimization problem for a pension fund under a hybrid model of stochastic volatility and constant elasticity of variance (CEV) using asymptotic analysis method. When the volatility component is fast mean-reverting, it is able to derive asymptotic approximations for the value function and the optimal strategy for general utility functions. Explicit solutions are given for the exponential and hyperbolic absolute risk aversion (HARA) utility functions. The study also shows that using the leading order optimal strategy results in the value function, not only up to the leading order, but also up to first order correction term. A practical strategy that does not depend on the unobservable volatility level is suggested. The result is an extension of the Merton's solution when stochastic volatility and elasticity of variance are considered simultaneously. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asymptotic%20analysis" title="asymptotic analysis">asymptotic analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=constant%20elasticity%20of%20variance" title=" constant elasticity of variance"> constant elasticity of variance</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title=" portfolio optimization"> portfolio optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20optimal%20control" title=" stochastic optimal control"> stochastic optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility" title=" stochastic volatility"> stochastic volatility</a> </p> <a href="https://publications.waset.org/abstracts/50103/portfolio-optimization-under-a-hybrid-stochastic-volatility-and-constant-elasticity-of-variance-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50103.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17102</span> Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maria%20C.%20Mariani">Maria C. Mariani</a>, <a href="https://publications.waset.org/abstracts/search?q=Md%20Al%20Masum%20Bhuiyan"> Md Al Masum Bhuiyan</a>, <a href="https://publications.waset.org/abstracts/search?q=Osei%20K.%20Tweneboah"> Osei K. Tweneboah</a>, <a href="https://publications.waset.org/abstracts/search?q=Hector%20G.%20Huizar"> Hector G. Huizar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Augmented%20Dickey%20Fuller%20Test" title="Augmented Dickey Fuller Test">Augmented Dickey Fuller Test</a>, <a href="https://publications.waset.org/abstracts/search?q=geophysical%20time%20series" title=" geophysical time series"> geophysical time series</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimation" title=" maximum likelihood estimation"> maximum likelihood estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model" title=" stochastic volatility model"> stochastic volatility model</a> </p> <a href="https://publications.waset.org/abstracts/75110/forecasting-the-volatility-of-geophysical-time-series-with-stochastic-volatility-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75110.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">315</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17101</span> Numerical Simulation of Wishart Diffusion Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Raphael%20Naryongo">Raphael Naryongo</a>, <a href="https://publications.waset.org/abstracts/search?q=Philip%20%20Ngare"> Philip Ngare</a>, <a href="https://publications.waset.org/abstracts/search?q=Anthony%20%20Waititu"> Anthony Waititu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with numerical simulation of Wishart processes for a single asset risky pricing model whose volatility is described by Wishart affine diffusion processes. The multi-factor specification of volatility will make the model more flexible enough to fit the stock market data for short or long maturities for better returns. The Wishart process is a stochastic process which is a positive semi-definite matrix-valued generalization of the square root process. The aim of the study is to model the log asset stock returns under the double Wishart stochastic volatility model. The solution of the log-asset return dynamics for Bi-Wishart processes will be obtained through Euler-Maruyama discretization schemes. The numerical results on the asset returns are compared to the existing models returns such as Heston stochastic volatility model and double Heston stochastic volatility model <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=euler%20schemes" title="euler schemes">euler schemes</a>, <a href="https://publications.waset.org/abstracts/search?q=log-asset%20return" title=" log-asset return"> log-asset return</a>, <a href="https://publications.waset.org/abstracts/search?q=infinitesimal%20generator" title=" infinitesimal generator"> infinitesimal generator</a>, <a href="https://publications.waset.org/abstracts/search?q=wishart%20diffusion%20affine%20processes" title=" wishart diffusion affine processes "> wishart diffusion affine processes </a> </p> <a href="https://publications.waset.org/abstracts/137631/numerical-simulation-of-wishart-diffusion-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137631.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">378</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17100</span> A Multivariate 4/2 Stochastic Covariance Model: Properties and Applications to Portfolio Decisions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuyang%20Cheng">Yuyang Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Marcos%20Escobar-Anel"> Marcos Escobar-Anel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stochastic%20covariance%20process" title="stochastic covariance process">stochastic covariance process</a>, <a href="https://publications.waset.org/abstracts/search?q=4%2F2%20stochastic%20volatility%20model" title=" 4/2 stochastic volatility model"> 4/2 stochastic volatility model</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20co-volatility%20movements" title=" stochastic co-volatility movements"> stochastic co-volatility movements</a>, <a href="https://publications.waset.org/abstracts/search?q=characteristic%20function" title=" characteristic function"> characteristic function</a>, <a href="https://publications.waset.org/abstracts/search?q=expected%20utility%20theory" title=" expected utility theory"> expected utility theory</a>, <a href="https://publications.waset.org/abstracts/search?q=veri%0Ccation%20theorem" title=" verication theorem"> verication theorem</a> </p> <a href="https://publications.waset.org/abstracts/153747/a-multivariate-42-stochastic-covariance-model-properties-and-applications-to-portfolio-decisions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153747.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">152</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17099</span> Evaluating the Effects of a Positive Bitcoin Shock on the U.S Economy: A TVP-FAVAR Model with Stochastic Volatility</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olfa%20Kaabia">Olfa Kaabia</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilyes%20Abid"> Ilyes Abid</a>, <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Guesmi"> Khaled Guesmi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This pioneer paper studies whether and how Bitcoin shocks are transmitted to the U.S economy. We employ a new methodology: TVP FAVAR model with stochastic volatility. We use a large dataset of 111 major U.S variables from 1959:m1 to 2016:m12. The results show that Bitcoin shocks significantly impact the U.S. economy. This significant impact is pronounced in a volatile and increasing U.S economy. The Bitcoin has a positive relationship on the U.S real activity, and a negative one on U.S prices and interest rates. Effects on the Monetary Policy exist via the inter-est rates and the Money, Credit and Finance transmission channels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bitcoin" title="bitcoin">bitcoin</a>, <a href="https://publications.waset.org/abstracts/search?q=US%20economy" title=" US economy"> US economy</a>, <a href="https://publications.waset.org/abstracts/search?q=FAVAR%20models" title=" FAVAR models"> FAVAR models</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility" title=" stochastic volatility"> stochastic volatility</a> </p> <a href="https://publications.waset.org/abstracts/78168/evaluating-the-effects-of-a-positive-bitcoin-shock-on-the-us-economy-a-tvp-favar-model-with-stochastic-volatility" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78168.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">247</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17098</span> A Stochastic Volatility Model for Optimal Market-Making</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zubier%20Arfan">Zubier Arfan</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20Johnson"> Paul Johnson </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=market-making" title="market-making">market-making</a>, <a href="https://publications.waset.org/abstracts/search?q=market-microsctrucure" title=" market-microsctrucure"> market-microsctrucure</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility" title=" stochastic volatility"> stochastic volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=quantitative%20trading" title=" quantitative trading "> quantitative trading </a> </p> <a href="https://publications.waset.org/abstracts/114281/a-stochastic-volatility-model-for-optimal-market-making" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114281.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17097</span> Hybrid Equity Warrants Pricing Formulation under Stochastic Dynamics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Teh%20Raihana%20Nazirah%20Roslan">Teh Raihana Nazirah Roslan</a>, <a href="https://publications.waset.org/abstracts/search?q=Siti%20Zulaiha%20Ibrahim"> Siti Zulaiha Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sharmila%20Karim"> Sharmila Karim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cox-Ingersoll-Ross%20model" title="Cox-Ingersoll-Ross model">Cox-Ingersoll-Ross model</a>, <a href="https://publications.waset.org/abstracts/search?q=equity%20warrants" title=" equity warrants"> equity warrants</a>, <a href="https://publications.waset.org/abstracts/search?q=Heston%20model" title=" Heston model"> Heston model</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20models" title=" hybrid models"> hybrid models</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic" title=" stochastic"> stochastic</a> </p> <a href="https://publications.waset.org/abstracts/124157/hybrid-equity-warrants-pricing-formulation-under-stochastic-dynamics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124157.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">129</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17096</span> Analysis of Financial Time Series by Using Ornstein-Uhlenbeck Type Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md%20Al%20Masum%20Bhuiyan">Md Al Masum Bhuiyan</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20C.%20Mariani"> Maria C. Mariani</a>, <a href="https://publications.waset.org/abstracts/search?q=Osei%20K.%20Tweneboah"> Osei K. Tweneboah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with 卤2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20time%20series" title="financial time series">financial time series</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimation" title=" maximum likelihood estimation"> maximum likelihood estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Ornstein-Uhlenbeck%20type%20models" title=" Ornstein-Uhlenbeck type models"> Ornstein-Uhlenbeck type models</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model" title=" stochastic volatility model"> stochastic volatility model</a> </p> <a href="https://publications.waset.org/abstracts/73856/analysis-of-financial-time-series-by-using-ornstein-uhlenbeck-type-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73856.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">241</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17095</span> Superiority of High Frequency Based Volatility Models: Empirical Evidence from an Emerging Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sibel%20Celik">Sibel Celik</a>, <a href="https://publications.waset.org/abstracts/search?q=H%C3%BCseyin%20Ergin"> H眉seyin Ergin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volatility" title="volatility">volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH%20model" title=" GARCH model"> GARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=realized%20volatility" title=" realized volatility"> realized volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20frequency%20data" title=" high frequency data"> high frequency data</a> </p> <a href="https://publications.waset.org/abstracts/18459/superiority-of-high-frequency-based-volatility-models-empirical-evidence-from-an-emerging-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18459.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">486</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17094</span> The Non-Uniqueness of Partial Differential Equations Options Price Valuation Formula for Heston Stochastic Volatility Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20D.%20Ibrahim">H. D. Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20C.%20Chinwenyi"> H. C. Chinwenyi</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Danjuma"> T. Danjuma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An option is defined as a financial contract that provides the holder the right but not the obligation to buy or sell a specified quantity of an underlying asset in the future at a fixed price (called a strike price) on or before the expiration date of the option. This paper examined two approaches for derivation of Partial Differential Equation (PDE) options price valuation formula for the Heston stochastic volatility model. We obtained various PDE option price valuation formulas using the riskless portfolio method and the application of Feynman-Kac theorem respectively. From the results obtained, we see that the two derived PDEs for Heston model are distinct and non-unique. This establishes the fact of incompleteness in the model for option price valuation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Black-Scholes%20partial%20differential%20equations" title="Black-Scholes partial differential equations">Black-Scholes partial differential equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Ito%20process" title=" Ito process"> Ito process</a>, <a href="https://publications.waset.org/abstracts/search?q=option%20price%20valuation" title=" option price valuation"> option price valuation</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20differential%20equations" title=" partial differential equations"> partial differential equations</a> </p> <a href="https://publications.waset.org/abstracts/131307/the-non-uniqueness-of-partial-differential-equations-options-price-valuation-formula-for-heston-stochastic-volatility-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131307.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">145</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17093</span> Modelling High-Frequency Crude Oil Dynamics Using Affine and Non-Affine Jump-Diffusion Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Katja%20Ignatieva">Katja Ignatieva</a>, <a href="https://publications.waset.org/abstracts/search?q=Patrick%20Wong"> Patrick Wong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility" title="stochastic volatility">stochastic volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=affine%20jump-diffusion%20models" title=" affine jump-diffusion models"> affine jump-diffusion models</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20frequency%20data" title=" high frequency data"> high frequency data</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20specification" title=" model specification"> model specification</a>, <a href="https://publications.waset.org/abstracts/search?q=markov%20chain%20monte%20carlo" title=" markov chain monte carlo"> markov chain monte carlo</a> </p> <a href="https://publications.waset.org/abstracts/159124/modelling-high-frequency-crude-oil-dynamics-using-affine-and-non-affine-jump-diffusion-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159124.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">104</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17092</span> Bayesian Value at Risk Forecast Using Realized Conditional Autoregressive Expectiel Mdodel with an Application of Cryptocurrency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Niya%20Chen">Niya Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Jennifer%20Chan"> Jennifer Chan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=expectile" title="expectile">expectile</a>, <a href="https://publications.waset.org/abstracts/search?q=CARE%20Model" title=" CARE Model"> CARE Model</a>, <a href="https://publications.waset.org/abstracts/search?q=CARR%20Model" title=" CARR Model"> CARR Model</a>, <a href="https://publications.waset.org/abstracts/search?q=quantile" title=" quantile"> quantile</a>, <a href="https://publications.waset.org/abstracts/search?q=cryptocurrency" title=" cryptocurrency"> cryptocurrency</a>, <a href="https://publications.waset.org/abstracts/search?q=Value%20at%20Risk" title=" Value at Risk"> Value at Risk</a> </p> <a href="https://publications.waset.org/abstracts/159362/bayesian-value-at-risk-forecast-using-realized-conditional-autoregressive-expectiel-mdodel-with-an-application-of-cryptocurrency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159362.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">109</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17091</span> Volatility Model with Markov Regime Switching to Forecast Baht/USD</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nop%20Sopipan">Nop Sopipan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volatility" title="volatility">volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20Regime%20Switching" title=" Markov Regime Switching"> Markov Regime Switching</a>, <a href="https://publications.waset.org/abstracts/search?q=forecasting" title=" forecasting"> forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=Baht%2FUSD" title=" Baht/USD"> Baht/USD</a> </p> <a href="https://publications.waset.org/abstracts/3942/volatility-model-with-markov-regime-switching-to-forecast-bahtusd" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3942.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17090</span> VaR Estimation Using the Informational Content of Futures Traded Volume</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amel%20Oueslati">Amel Oueslati</a>, <a href="https://publications.waset.org/abstracts/search?q=Olfa%20Benouda"> Olfa Benouda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> New Value at Risk (VaR) estimation is proposed and investigated. The well-known two stages Garch-EVT approach uses conditional volatility to generate one step ahead forecasts of VaR. With daily data for twelve stocks that decompose the Dow Jones Industrial Average (DJIA) index, this paper incorporates the volume in the first stage volatility estimation. Afterwards, the forecasting ability of this conditional volatility concerning the VaR estimation is compared to that of a basic volatility model without considering any trading component. The results are significant and bring out the importance of the trading volume in the VaR measure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Garch-EVT" title="Garch-EVT">Garch-EVT</a>, <a href="https://publications.waset.org/abstracts/search?q=value%20at%20risk" title=" value at risk"> value at risk</a>, <a href="https://publications.waset.org/abstracts/search?q=volume" title=" volume"> volume</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a> </p> <a href="https://publications.waset.org/abstracts/56021/var-estimation-using-the-informational-content-of-futures-traded-volume" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56021.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">285</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17089</span> Normalizing Logarithms of Realized Volatility in an ARFIMA Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20L.%20C.%20Yap">G. L. C. Yap</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process" title="Gaussian process">Gaussian process</a>, <a href="https://publications.waset.org/abstracts/search?q=long-memory" title=" long-memory"> long-memory</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=value-at-risk" title=" value-at-risk"> value-at-risk</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=Whittle%20estimator" title=" Whittle estimator"> Whittle estimator</a> </p> <a href="https://publications.waset.org/abstracts/58573/normalizing-logarithms-of-realized-volatility-in-an-arfima-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58573.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17088</span> Volatility Spillover Among the Stock Markets of South Asian Countries</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tariq%20Aziz">Tariq Aziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Suresh%20Kumar"> Suresh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Vikesh%20Kumar"> Vikesh Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Sheraz%20Mustafa"> Sheraz Mustafa</a>, <a href="https://publications.waset.org/abstracts/search?q=Jhanzeb%20Marwat"> Jhanzeb Marwat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper provides an updated version of volatility spillover among the equity markets of South Asian countries, including Pakistan, India, Srilanka, and Bangladesh. The analysis uses both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedasticity models to investigate volatility persistence and leverage effect. The bivariate EGARCH model is used to test for volatility transmission between two equity markets. Weekly data for the period February 2013 to August 2019 is used for empirical analysis. The findings indicate that the leverage effect exists in the equity markets of all the countries except Bangladesh. The volatility spillover from the equity market of Bangladesh to all other countries is negative and significant whereas the volatility of the equity market of Sri-Lanka does influence the volatility of any other country鈥檚 equity market. Indian equity market influence only the volatility of the Sri-Lankan equity market; and there is bidirectional volatility spillover between the equity markets of Pakistan and Bangladesh. The findings are important for policy-makers and international investors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=volatility%20spillover" title="volatility spillover">volatility spillover</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility%20persistence" title=" volatility persistence"> volatility persistence</a>, <a href="https://publications.waset.org/abstracts/search?q=garch" title=" garch"> garch</a>, <a href="https://publications.waset.org/abstracts/search?q=egarch" title=" egarch"> egarch</a> </p> <a href="https://publications.waset.org/abstracts/121891/volatility-spillover-among-the-stock-markets-of-south-asian-countries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121891.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">139</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17087</span> The Response of the Central Bank to the Exchange Rate Movement: A Dynamic Stochastic General Equilibrium-Vector Autoregressive Approach for Tunisian Economy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelli%20Soulaima">Abdelli Soulaima</a>, <a href="https://publications.waset.org/abstracts/search?q=Belhadj%20Besma"> Belhadj Besma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper examines the choice of the central bank toward the movements of the nominal exchange rate and evaluates its effects on the volatility of the output growth and the in铿俛tion. The novel hybrid method of the dynamic stochastic general equilibrium called the DSGE-VAR is proposed for analyzing this policy experiment in a small scale open economy in particular Tunisia. The contribution is provided to the empirical literature as we apply the Tunisian data with this model, which is rarely used in this context. Note additionally that the issue of treating the degree of response of the central bank to the exchange rate in Tunisia is special. To ameliorate the estimation, the Bayesian technique is carried out for the sample 1980:q1 to 2011 q4. Our results reveal that the central bank should not react or softly react to the exchange rate. The variance decomposition displayed that the overall inflation volatility is more pronounced with the fixed exchange rate regime for most of the shocks except for the productivity and the interest rate. The output volatility is also higher with this regime with the majority of the shocks exempting the foreign interest rate and the interest rate shocks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DSGE-VAR%20modeling" title="DSGE-VAR modeling">DSGE-VAR modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=exchange%20rate" title=" exchange rate"> exchange rate</a>, <a href="https://publications.waset.org/abstracts/search?q=monetary%20policy" title=" monetary policy"> monetary policy</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20estimation" title=" Bayesian estimation"> Bayesian estimation</a> </p> <a href="https://publications.waset.org/abstracts/43655/the-response-of-the-central-bank-to-the-exchange-rate-movement-a-dynamic-stochastic-general-equilibrium-vector-autoregressive-approach-for-tunisian-economy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43655.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">295</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17086</span> The Investigation of Oil Price Shocks by Using a Dynamic Stochastic General Equilibrium: The Case of Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bahram%20Fathi">Bahram Fathi</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Alizadeh"> Karim Alizadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Azam%20Mohammadbagheri"> Azam Mohammadbagheri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model鈥檚 robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oil%20price" title="oil price">oil price</a>, <a href="https://publications.waset.org/abstracts/search?q=shocks" title=" shocks"> shocks</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20stochastic%20general%20equilibrium" title=" dynamic stochastic general equilibrium"> dynamic stochastic general equilibrium</a>, <a href="https://publications.waset.org/abstracts/search?q=Iran" title=" Iran"> Iran</a> </p> <a href="https://publications.waset.org/abstracts/27775/the-investigation-of-oil-price-shocks-by-using-a-dynamic-stochastic-general-equilibrium-the-case-of-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27775.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">438</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17085</span> Structural Breaks, Asymmetric Effects and Long Memory in the Volatility of Turkey Stock Market </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Serpil%20T%C3%BCrky%C4%B1lmaz">Serpil T眉rky谋lmaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Mesut%20Bal%C4%B1bey"> Mesut Bal谋bey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, long memory properties in volatility of Turkey Stock Market are being examined through the FIGARCH, FIEGARCH and FIAPARCH models under different distribution assumptions as normal and skewed student-t distributions. Furthermore, structural changes in volatility of Turkey Stock Market are investigated. The results display long memory property and the presence of asymmetric effects of shocks in volatility of Turkey Stock Market. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FIAPARCH%20model" title="FIAPARCH model">FIAPARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=FIEGARCH%20model" title=" FIEGARCH model"> FIEGARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=FIGARCH%20model" title=" FIGARCH model"> FIGARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20break" title=" structural break"> structural break</a> </p> <a href="https://publications.waset.org/abstracts/14438/structural-breaks-asymmetric-effects-and-long-memory-in-the-volatility-of-turkey-stock-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">291</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17084</span> Finding DEA Targets Using Multi-Objective Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farzad%20Sharifi">Farzad Sharifi</a>, <a href="https://publications.waset.org/abstracts/search?q=Raziyeh%20Shamsi"> Raziyeh Shamsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose molti-objective DEA-R model, because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduces the efficiency score), an efficient DMU is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other case, only the ratio of stochastic data may be available (e.g; the ratio of stochastic inputs to stochastic outputs). Thus, we provide multi objective DEA model without explicit outputs and prove that in-put oriented MOP DEA-R model in the invariable return to scale case can be replacing by MOP- DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model, yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DEA" title="DEA">DEA</a>, <a href="https://publications.waset.org/abstracts/search?q=MOLP" title=" MOLP"> MOLP</a>, <a href="https://publications.waset.org/abstracts/search?q=STOCHASTIC" title=" STOCHASTIC"> STOCHASTIC</a>, <a href="https://publications.waset.org/abstracts/search?q=DEA-R" title=" DEA-R"> DEA-R</a> </p> <a href="https://publications.waset.org/abstracts/59723/finding-dea-targets-using-multi-objective-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59723.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17083</span> Comparison Study of Capital Protection Risk Management Strategies: Constant Proportion Portfolio Insurance versus Volatility Target Based Investment Strategy with a Guarantee</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olga%20Biedova">Olga Biedova</a>, <a href="https://publications.waset.org/abstracts/search?q=Victoria%20Steblovskaya"> Victoria Steblovskaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai%20Wallbaum"> Kai Wallbaum</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the current capital market environment, investors constantly face the challenge of finding a successful and stable investment mechanism. Highly volatile equity markets and extremely low bond returns bring about the demand for sophisticated yet reliable risk management strategies. Investors are looking for risk management solutions to efficiently protect their investments. This study compares a classic Constant Proportion Portfolio Insurance (CPPI) strategy to a Volatility Target portfolio insurance (VTPI). VTPI is an extension of the well-known Option Based Portfolio Insurance (OBPI) to the case where an embedded option is linked not to a pure risky asset such as e.g., S&P 500, but to a Volatility Target (VolTarget) portfolio. VolTarget strategy is a recently emerged rule-based dynamic asset allocation mechanism where the portfolio鈥檚 volatility is kept under control. As a result, a typical VTPI strategy allows higher participation rates in the market due to reduced embedded option prices. In addition, controlled volatility levels eliminate the volatility spread in option pricing, one of the frequently cited reasons for OBPI strategy fall behind CPPI. The strategies are compared within the framework of the stochastic dominance theory based on numerical simulations, rather than on the restrictive assumption of the Black-Scholes type dynamics of the underlying asset. An extended comparative quantitative analysis of performances of the above investment strategies in various market scenarios and within a range of input parameter values is presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CPPI" title="CPPI">CPPI</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20insurance" title=" portfolio insurance"> portfolio insurance</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20dominance" title=" stochastic dominance"> stochastic dominance</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility%20target" title=" volatility target"> volatility target</a> </p> <a href="https://publications.waset.org/abstracts/83288/comparison-study-of-capital-protection-risk-management-strategies-constant-proportion-portfolio-insurance-versus-volatility-target-based-investment-strategy-with-a-guarantee" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83288.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17082</span> Long- and Short-Term Impacts of COVID-19 and Gold Price on Price Volatility: A Comparative Study of MIDAS and GARCH-MIDAS Models for USA Crude Oil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samir%20K.%20Safi">Samir K. Safi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GARCH-MIDAS" title="GARCH-MIDAS">GARCH-MIDAS</a>, <a href="https://publications.waset.org/abstracts/search?q=MIDAS" title=" MIDAS"> MIDAS</a>, <a href="https://publications.waset.org/abstracts/search?q=crude%20oil" title=" crude oil"> crude oil</a>, <a href="https://publications.waset.org/abstracts/search?q=gold" title=" gold"> gold</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title=" COVID-19"> COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a> </p> <a href="https://publications.waset.org/abstracts/184880/long-and-short-term-impacts-of-covid-19-and-gold-price-on-price-volatility-a-comparative-study-of-midas-and-garch-midas-models-for-usa-crude-oil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184880.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">65</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17081</span> Finding Data Envelopment Analysis Targets Using Multi-Objective Programming in DEA-R with Stochastic Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Shamsi">R. Shamsi</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Sharifi"> F. Sharifi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DEA-R" title="DEA-R">DEA-R</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objective%20programming" title=" multi-objective programming"> multi-objective programming</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20data" title=" stochastic data"> stochastic data</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20envelopment%20analysis" title=" data envelopment analysis"> data envelopment analysis</a> </p> <a href="https://publications.waset.org/abstracts/154613/finding-data-envelopment-analysis-targets-using-multi-objective-programming-in-dea-r-with-stochastic-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/154613.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">105</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17080</span> Co-integration for Soft Commodities with Non-Constant Volatility</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Channol">E. Channol</a>, <a href="https://publications.waset.org/abstracts/search?q=O.%20Collet"> O. Collet</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Kostyuchyk"> N. Kostyuchyk</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Mesbah"> T. Mesbah</a>, <a href="https://publications.waset.org/abstracts/search?q=Quoc%20Hoang%20Long%20Nguyen"> Quoc Hoang Long Nguyen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a pricing model is proposed for co-integrated commodities extending Larsson model. The futures formulae have been derived and tests have been performed with non-constant volatility. The model has been applied to energy commodities (gas, CO2, energy) and soft commodities (corn, wheat). Results show that non-constant volatility leads to more accurate short term prices, which provides better evaluation of value-at-risk and more generally improve the risk management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=co-integration" title="co-integration">co-integration</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20commodities" title=" soft commodities"> soft commodities</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title=" risk management"> risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=value-at-risk" title=" value-at-risk"> value-at-risk</a> </p> <a href="https://publications.waset.org/abstracts/11078/co-integration-for-soft-commodities-with-non-constant-volatility" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11078.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">547</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17079</span> Markov Switching of Conditional Variance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Josip%20Arneric">Josip Arneric</a>, <a href="https://publications.waset.org/abstracts/search?q=Blanka%20Skrabic%20Peric"> Blanka Skrabic Peric</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emerging%20markets" title="emerging markets">emerging markets</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20switching" title=" Markov switching"> Markov switching</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH%20model" title=" GARCH model"> GARCH model</a>, <a href="https://publications.waset.org/abstracts/search?q=transition%20probabilities" title=" transition probabilities"> transition probabilities</a> </p> <a href="https://publications.waset.org/abstracts/23987/markov-switching-of-conditional-variance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23987.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">455</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17078</span> Volatility Transmission between Oil Price and Stock Return of Emerging and Developed Countries</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Algia%20Hammami">Algia Hammami</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelfatteh%20Bouri"> Abdelfatteh Bouri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, our objective is to study the transmission of volatility between oil and stock markets in developed (USA, Germany, Italy, France and Japan) and emerging countries (Tunisia, Thailand, Brazil, Argentina, and Jordan) for the period 1998-2015. Our methodology consists of analyzing the monthly data by the GARCH-BEKK model to capture the effect in terms of volatility in the variation of the oil price on the different stock market. The empirical results in the emerging countries indicate that the relationships are unidirectional from the stock market to the oil market. For the developed countries, we find that the transmission of volatility is unidirectional from the oil market to stock market. For the USA and Italy, we find no transmission between the two markets. The transmission is bi-directional only in Thailand. Following our estimates, we also noticed that the emerging countries influence almost the same extent as the developed countries, while at the transmission of volatility there a bid difference. The GARCH-BEKK model is more effective than the others versions to minimize the risk of an oil-stock portfolio. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=GARCH" title="GARCH">GARCH</a>, <a href="https://publications.waset.org/abstracts/search?q=oil%20prices" title=" oil prices"> oil prices</a>, <a href="https://publications.waset.org/abstracts/search?q=stock%20market" title=" stock market"> stock market</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility%20transmission" title=" volatility transmission"> volatility transmission</a> </p> <a href="https://publications.waset.org/abstracts/64379/volatility-transmission-between-oil-price-and-stock-return-of-emerging-and-developed-countries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64379.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">437</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17077</span> Forecasting Silver Commodity Prices Using Geometric Brownian Motion: A Stochastic Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sina%20Dehghani">Sina Dehghani</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhikang%20Rong"> Zhikang Rong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Historically, a variety of approaches have been taken to forecast commodity prices due to the significant implications of these values on the global economy. An accurate forecasting tool for a valuable commodity would significantly benefit investors and governmental agencies. Silver, in particular, has grown significantly as a commodity in recent years due to its use in healthcare and technology. This manuscript aims to utilize the Geometric Brownian Motion predictive model to forecast silver commodity prices over multiple 3-year periods. The results of the study indicate that the model has several limitations, particularly its inability to work effectively over longer periods of time, but still was extremely effective over shorter time frames. This study sets a baseline for silver commodity forecasting with GBM, and the model could be further strengthened with refinement. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=geometric%20Brownian%20motion" title="geometric Brownian motion">geometric Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=commodity" title=" commodity"> commodity</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20management" title=" risk management"> risk management</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility" title=" volatility"> volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20behavior" title=" stochastic behavior"> stochastic behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=price%20forecasting" title=" price forecasting"> price forecasting</a> </p> <a href="https://publications.waset.org/abstracts/192474/forecasting-silver-commodity-prices-using-geometric-brownian-motion-a-stochastic-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192474.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">23</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17076</span> Leverage Effect for Volatility with Generalized Laplace Error</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farrukh%20Javed">Farrukh Javed</a>, <a href="https://publications.waset.org/abstracts/search?q=Krzysztof%20Podg%C3%B3rski"> Krzysztof Podg贸rski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heavy%20tails" title="heavy tails">heavy tails</a>, <a href="https://publications.waset.org/abstracts/search?q=volatility%20clustering" title=" volatility clustering"> volatility clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20asymmetric%20laplace%20distribution" title=" generalized asymmetric laplace distribution"> generalized asymmetric laplace distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=leverage%20effect" title=" leverage effect"> leverage effect</a>, <a href="https://publications.waset.org/abstracts/search?q=conditional%20heteroskedasticity" title=" conditional heteroskedasticity"> conditional heteroskedasticity</a>, <a href="https://publications.waset.org/abstracts/search?q=asymmetric%20power%20volatility" title=" asymmetric power volatility"> asymmetric power volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=GARCH%20models" title=" GARCH models "> GARCH models </a> </p> <a href="https://publications.waset.org/abstracts/18972/leverage-effect-for-volatility-with-generalized-laplace-error" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18972.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">385</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17075</span> The Relationship between Top Management Replacement and Risk, Sale and Cash Volatilities with Respect to Unqualified Audit Opinion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Dasineh">Mehdi Dasineh</a>, <a href="https://publications.waset.org/abstracts/search?q=Yadollah%20Tariverdi"> Yadollah Tariverdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Marzieh%20H.%20Takhti"> Marzieh H. Takhti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigated the relationship between top management turnover with risk volatility, sale volatility and fluctuations in the company's cash depending on the unqualified audit report in Tehran Stock Exchange (TSE). In this study, we examined 104 firms over the period 2009-2014 which were selected from (TSE). There was 624 observed year-company data in this research. Hypotheses of this research have been evaluated by using regression tests for example F-statistical and Durbin-Watson. Based on our sample we found significant relationship between top management replacement and risk volatility, sale Volatility and cash volatility with tendency unqualified audit opinion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=top%20management%20replacement" title="top management replacement">top management replacement</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20volatility" title=" risk volatility"> risk volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=sale%20volatility" title=" sale volatility"> sale volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=cash%20volatility" title=" cash volatility"> cash volatility</a>, <a href="https://publications.waset.org/abstracts/search?q=unqualified%20audit%20opinion" title=" unqualified audit opinion"> unqualified audit opinion</a> </p> <a href="https://publications.waset.org/abstracts/45022/the-relationship-between-top-management-replacement-and-risk-sale-and-cash-volatilities-with-respect-to-unqualified-audit-opinion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45022.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">282</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=6">6</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=7">7</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=8">8</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=9">9</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=10">10</a></li> <li class="page-item disabled"><span class="page-link">...</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=570">570</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=571">571</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); });*/ jQuery.get({ url: "https://publications.waset.org/xhr/user-menu", cache: false }).then(function(response){ jQuery('#mainNavMenu').append(response); }); }); </script> </body> </html>