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<a href=/list/q-fin/new?skip=0&show=1000 rel="nofollow"> fewer</a> | <span style="color: #454545">more</span> | <span style="color: #454545">all</span> </div> <dl id='articles'> <h3>New submissions (showing 5 of 5 entries)</h3> <dt> <a name='item1'>[1]</a> <a href ="/abs/2504.01041" title="Abstract" id="2504.01041"> arXiv:2504.01041 </a> [<a href="/pdf/2504.01041" title="Download PDF" id="pdf-2504.01041" aria-labelledby="pdf-2504.01041">pdf</a>, <a href="/format/2504.01041" title="Other formats" id="oth-2504.01041" aria-labelledby="oth-2504.01041">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Empirical Analysis of Digital Innovations Impact on Corporate ESG Performance: The Mediating Role of GAI Technology </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Cui,+J">Jun Cui</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span>; Computers and Society (cs.CY) </div> <p class='mathjax'> This study investigates the relationship between corporate digital innovation and Environmental, Social, and Governance (ESG) performance, with a specific focus on the mediating role of Generative artificial intelligence technology adoption. Using a comprehensive panel dataset of 8,000 observations from the CMARS and WIND database spanning from 2015 to 2023, we employ multiple econometric techniques to examine this relationship. Our findings reveal that digital innovation significantly enhances corporate ESG performance, with GAI technology adoption serving as a crucial mediating mechanism. Specifically, digital innovation positively influences GAI technology adoption, which subsequently improves ESG performance. Furthermore, our heterogeneity analysis indicates that this relationship varies across firm size, industry type, and ownership structure. Finally, our results remain robust after addressing potential endogeneity concerns through instrumental variable estimation, propensity score matching, and differenc in differences approaches. This research contributes to the growing literature on technologydriven sustainability transformations and offers practical implications for corporate strategy and policy development in promoting sustainable business practices through technological advancement. </p> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/2504.01051" title="Abstract" id="2504.01051"> arXiv:2504.01051 </a> [<a href="/pdf/2504.01051" title="Download PDF" id="pdf-2504.01051" aria-labelledby="pdf-2504.01051">pdf</a>, <a href="https://arxiv.org/html/2504.01051v1" title="View HTML" id="html-2504.01051" aria-labelledby="html-2504.01051" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2504.01051" title="Other formats" id="oth-2504.01051" aria-labelledby="oth-2504.01051">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exploitation of Eurosystem Loopholes and Their Quantitative Reconstruction </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Svozil,+K">Karl Svozil</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 6 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Economic Affairs, 45(1), 17-26 (2025) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> This paper identifies and analyzes six key strategies used to exploit the Eurosystem's financial mechanisms, and attempts a quantitative reconstruction: inflating TARGET balances, leveraging collateral swaps followed by defaults, diluting self-imposed regulatory rules, issuing money through Emergency Liquidity Assistance (ELA), acquisitions facilitated via the Agreement on Net Financial Assets (ANFA), and the perpetual (re)issuance of sovereign bonds as collateral. The paper argues that these practices stem from systemic vulnerabilities or deliberate opportunism within the Eurosystem. While it does not advocate for illicit activities, the paper highlights significant weaknesses in the current structure and concludes that comprehensive reforms are urgently needed. </p> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/2504.01138" title="Abstract" id="2504.01138"> arXiv:2504.01138 </a> [<a href="/pdf/2504.01138" title="Download PDF" id="pdf-2504.01138" aria-labelledby="pdf-2504.01138">pdf</a>, <a href="/format/2504.01138" title="Other formats" id="oth-2504.01138" aria-labelledby="oth-2504.01138">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The role of ethical consumption in promoting democratic sustainability: revisiting neoclassical economics through Kantian ethics </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Stiefenhofer,+P">Pascal Stiefenhofer</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 42 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> This paper explores how ethical consumption can transform democratic governance toward sustainability by challenging traditional economic models centered on utility and efficiency. As societal values shift toward transparency equity and environmental responsibility ethical consumers increasingly influence markets. Drawing on Whites Kantian economic framework and Ingleharts theory of value change the paper proposes a model integrating moral imperatives into economic theory. Using a vector bundle approach it captures evolving ethical preferences advocating for an inclusive sustainability focused economic paradigm aligned with post materialist values. </p> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/2504.01566" title="Abstract" id="2504.01566"> arXiv:2504.01566 </a> [<a href="/pdf/2504.01566" title="Download PDF" id="pdf-2504.01566" aria-labelledby="pdf-2504.01566">pdf</a>, <a href="https://arxiv.org/html/2504.01566v1" title="View HTML" id="html-2504.01566" aria-labelledby="html-2504.01566" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2504.01566" title="Other formats" id="oth-2504.01566" aria-labelledby="oth-2504.01566">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> GPT Adoption and the Impact of Disclosure Policies </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Yang,+C">Cathy Yang</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Amariles,+D+R">David Restrepo Amariles</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Allen,+L">Leo Allen</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Troussel,+A">Aurore Troussel</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> Generative Pre-trained Transformers (GPTs), particularly Large Language Models (LLMs) like ChatGPT, have proven effective in content generation and productivity enhancement. However, legal risks associated with these tools lead to adoption variance and concealment of AI use within organizations. This study examines the impact of disclosure on ChatGPT adoption in legal, audit and advisory roles in consulting firms through the lens of agency theory. We conducted a survey experiment to evaluate agency costs in the context of unregulated corporate use of ChatGPT, with a particular focus on how mandatory disclosure influences information asymmetry and misaligned interests. Our findings indicate that in the absence of corporate regulations, such as an AI policy, firms may incur agency costs, which can hinder the full benefits of GPT adoption. While disclosure policies reduce information asymmetry, they do not significantly lower overall agency costs due to managers undervaluing analysts' contributions with GPT use. Finally, we examine the scope of existing regulations in Europe and the United States regarding disclosure requirements, explore the sharing of risk and responsibility within firms, and analyze how incentive mechanisms promote responsible AI adoption. </p> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/2504.01756" title="Abstract" id="2504.01756"> arXiv:2504.01756 </a> [<a href="/pdf/2504.01756" title="Download PDF" id="pdf-2504.01756" aria-labelledby="pdf-2504.01756">pdf</a>, <a href="/format/2504.01756" title="Other formats" id="oth-2504.01756" aria-labelledby="oth-2504.01756">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Renewable Diesel Boom: The Impact of Soybean Crush Plants on Local Soybean Basis </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Wu,+S">Shujie Wu</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Mallory,+M">Mindy Mallory</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Serra,+T">Teresa Serra</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> We investigate the impact of the policy-driven expansion of the diesel and renewable diesel industry on local soybean prices. Because soybean oil is a key feedstock for biodiesel and renewable diesel, significant investments have been made in new soybean crush facilities and the expansion of existing ones. We quantify the effect of both new and existing soybean plants on soybean basis using panel data and a differences-in-difference approach. The data available on new plants does not allow us to identify any statistically significant impacts. However, existing plants increase the basis by 23.36 to 9.20 cents per bushel, with the effect diminishing with distance. These results suggest the relevance of biofuel policies in supporting rural economies and have relevant policy implications. </p> </div> </dd> </dl> <dl id='articles'> <h3>Cross submissions (showing 2 of 2 entries)</h3> <dt> <a name='item6'>[6]</a> <a href ="/abs/2504.01033" title="Abstract" id="2504.01033"> arXiv:2504.01033 </a> (cross-list from physics.ao-ph) [<a href="/pdf/2504.01033" title="Download PDF" id="pdf-2504.01033" aria-labelledby="pdf-2504.01033">pdf</a>, <a href="/format/2504.01033" title="Other formats" id="oth-2504.01033" aria-labelledby="oth-2504.01033">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Slowing Climate Change and Ocean Acidification by Converting Atmospheric Carbon Dioxide to Graphite (CD2G) </div> <div class='list-authors'><a href="https://arxiv.org/search/physics?searchtype=author&query=Harrison,+K+G">Kevin Geyer Harrison</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 39 pages, 6 figures, 5 tables, 6 appendices </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Atmospheric and Oceanic Physics (physics.ao-ph)</span>; General Economics (econ.GN) </div> <p class='mathjax'> Removing carbon dioxide from the atmosphere may slow climate change and ocean acidification. My approach converts atmospheric carbon dioxide into graphite (CD2G). The net profit for this conversion is ~$381/ton CO2 removed from the atmosphere. At the gigaton scale, CD2G factories will increase the affordability and availability of graphite. Since graphite can be used to make thermal batteries and electrodes for fuel cells and batteries, CD2G factories will help lower the cost of storing renewable energy, which will accelerate the transition to renewable energy. Replacing fossil fuel energy with renewable energy will slow the release of carbon dioxide to the atmosphere, also slowing climate change. Converting atmospheric carbon dioxide into graphite will both generate a profit and slow climate change. </p> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/2504.01474" title="Abstract" id="2504.01474"> arXiv:2504.01474 </a> (cross-list from math.OC) [<a href="/pdf/2504.01474" title="Download PDF" id="pdf-2504.01474" aria-labelledby="pdf-2504.01474">pdf</a>, <a href="https://arxiv.org/html/2504.01474v1" title="View HTML" id="html-2504.01474" aria-labelledby="html-2504.01474" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2504.01474" title="Other formats" id="oth-2504.01474" aria-labelledby="oth-2504.01474">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Dual first-order methods for efficient computation of convex hull prices </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Tanji,+S">Sofiane Tanji</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Kamri,+Y">Yassine Kamri</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Glineur,+F">Fran莽ois Glineur</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Madani,+M">Mehdi Madani</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 10 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Optimization and Control (math.OC)</span>; General Economics (econ.GN); Systems and Control (eess.SY) </div> <p class='mathjax'> Convex Hull (CH) pricing, used in US electricity markets and raising interest in Europe, is a pricing rule designed to handle markets with non-convexities such as startup costs and minimum up and down times. In such markets, the market operator makes side payments to generators to cover lost opportunity costs, and CH prices minimize the total "lost opportunity costs", which include both actual losses and missed profit opportunities. These prices can also be obtained by solving a (partial) Lagrangian dual of the original mixed-integer program, where power balance constraints are dualized. Computing CH prices then amounts to minimizing a sum of nonsmooth convex objective functions, where each term depends only on a single generator. The subgradient of each of those terms can be obtained independently by solving smaller mixed-integer programs. In this work, we benchmark a large panel of first-order methods to solve the above dual CH pricing problem. We test several dual methods, most of which not previously considered for CH pricing, namely a proximal variant of the bundle level method, subgradient methods with three different stepsize strategies, two recent parameter-free methods and an accelerated gradient method combined with smoothing. We compare those methods on two representative sets of real-world large-scale instances and complement the comparison with a (Dantzig-Wolfe) primal column generation method shown to be efficient at computing CH prices, for reference. Our numerical experiments show that the bundle proximal level method and two variants of the subgradient method perform the best among all dual methods and compare favorably with the Dantzig-Wolfe primal method. </p> </div> </dd> </dl> <dl id='articles'> <h3>Replacement submissions (showing 12 of 12 entries)</h3> <dt> <a name='item8'>[8]</a> <a href ="/abs/2308.10313" title="Abstract" id="2308.10313"> arXiv:2308.10313 </a> (replaced) [<a href="/pdf/2308.10313" title="Download PDF" id="pdf-2308.10313" aria-labelledby="pdf-2308.10313">pdf</a>, <a href="/format/2308.10313" title="Other formats" id="oth-2308.10313" aria-labelledby="oth-2308.10313">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Exploring the Role of Perceived Range Anxiety in Adoption Behavior of Plug-in Electric Vehicles </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Nazari,+F">Fatemeh Nazari</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Mohammadian,+A">Abolfazl Mohammadian</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 3 figures, 5 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> A sustainable solution to negative externalities imposed by road transportation is replacing internal combustion vehicles with electric vehicles (EVs), especially plug-in EV (PEV) encompassing plug-in hybrid EV (PHEV) and battery EV (BEV). However, EV market share is still low and is forecast to remain low and uncertain. This shows a research need for an in-depth understanding of EV adoption behavior with a focus on one of the main barriers to the mass EV adoption, which is the limited electric driving range. The present study extends the existing literature in two directions; First, the influence of the psychological aspect of driving range, which is referred to as range anxiety, is explored on EV adoption behavior by presenting a nested logit (NL) model with a latent construct. Second, the two-level NL model captures individuals' decision on EV adoption behavior distinguished by vehicle transaction type and EV type, where the upper level yields the vehicle transaction type selected from the set of alternatives including no-transaction, sell, trade, and add. The fuel type of the vehicles decided to be acquired, either as traded-for or added vehicles, is simultaneously determined at the lower level from a set including conventional vehicle, hybrid EV, PHEV, and BEV. The model is empirically estimated using a stated preferences dataset collected in the State of California. A notable finding is that anxiety about driving range influences the preference for BEV, especially as an added than traded-for vehicle, but not the decision on PHEV adoption. </p> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/2404.03794" title="Abstract" id="2404.03794"> arXiv:2404.03794 </a> (replaced) [<a href="/pdf/2404.03794" title="Download PDF" id="pdf-2404.03794" aria-labelledby="pdf-2404.03794">pdf</a>, <a href="https://arxiv.org/html/2404.03794v2" title="View HTML" id="html-2404.03794" aria-labelledby="html-2404.03794" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2404.03794" title="Other formats" id="oth-2404.03794" aria-labelledby="oth-2404.03794">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Effect of State and Local Sexual Orientation Anti-Discrimination Laws on Labor Market Differentials </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Delhommer,+S">Scott Delhommer</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Vamossy,+D+F">Domonkos F. Vamossy</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> This paper presents the first quasi-experimental research examining the effect of both local and state anti-discrimination laws on sexual orientation on the labor supply and wages of lesbian, gay, and bisexual (LGB) workers. To do so, we use the American Community Survey data on household composition to infer sexual orientation and combine this with a unique panel dataset on state and local anti-discrimination laws. Leveraging variation in law implementation across localities over time and between same-sex and different-sex couples, we find that anti-discrimination laws not only significantly narrow gaps in labor force participation and employment for male same-sex couples relative to men in different-sex couples, but also boost their percentile rank in the wage distribution. Our analysis reveals mostly null effects for female same-sex couples; however, in metropolitan areas these laws significantly reduce their employment compared to women in different-sex couples. One explanation for the reduced labor supply is that female same-sex couples begin to have more children in response to the laws. Finally, we present evidence that state anti-discrimination laws significantly and persistently increased support for same-sex marriage. This research shows that anti-discrimination laws can be an effective policy tool for reducing labor market inequalities across sexual orientation and improving sentiment toward LGB Americans. </p> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/2406.20063" title="Abstract" id="2406.20063"> arXiv:2406.20063 </a> (replaced) [<a href="/pdf/2406.20063" title="Download PDF" id="pdf-2406.20063" aria-labelledby="pdf-2406.20063">pdf</a>, <a href="https://arxiv.org/html/2406.20063v3" title="View HTML" id="html-2406.20063" aria-labelledby="html-2406.20063" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2406.20063" title="Other formats" id="oth-2406.20063" aria-labelledby="oth-2406.20063">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal consumption under loss-averse multiplicative habit-formation preferences </div> <div class='list-authors'><a href="https://arxiv.org/search/q-fin?searchtype=author&query=Angoshtari,+B">Bahman Angoshtari</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Yu,+X">Xiang Yu</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Yuan,+F">Fengyi Yuan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 42 pages, 10 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Mathematical Finance (q-fin.MF)</span>; Portfolio Management (q-fin.PM) </div> <p class='mathjax'> This paper studies a loss-averse version of the multiplicative habit formation preference and the corresponding optimal investment and consumption strategies over an infinite horizon. The agent's consumption preference is depicted by a general S-shaped utility function of her consumption-to-habit ratio. By considering the concave envelope of the S-shaped utility and the associated dual value function, we provide a thorough analysis of the HJB equation for the concavified problem via studying a related nonlinear free boundary problem. Based on established properties of the solution to this free boundary problem, we obtain the optimal consumption and investment policies in feedback form. Some new and technical verification arguments are developed to cope with generality of the utility function. The equivalence between the original problem and the concavified problem readily follows from the structure of the feedback controls. We also discuss some quantitative properties of the optimal policies, complemented by illustrative numerical examples and their financial implications. </p> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/2409.06289" title="Abstract" id="2409.06289"> arXiv:2409.06289 </a> (replaced) [<a href="/pdf/2409.06289" title="Download PDF" id="pdf-2409.06289" aria-labelledby="pdf-2409.06289">pdf</a>, <a href="https://arxiv.org/html/2409.06289v2" title="View HTML" id="html-2409.06289" aria-labelledby="html-2409.06289" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2409.06289" title="Other formats" id="oth-2409.06289" aria-labelledby="oth-2409.06289">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Automate Strategy Finding with LLM in Quant Investment </div> <div class='list-authors'><a href="https://arxiv.org/search/q-fin?searchtype=author&query=Kou,+Z">Zhizhuo Kou</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Yu,+H">Holam Yu</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Luo,+J">Junyu Luo</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Peng,+J">Jingshu Peng</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Chen,+L">Lei Chen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Portfolio Management (q-fin.PM)</span>; Machine Learning (cs.LG); Pricing of Securities (q-fin.PR) </div> <p class='mathjax'> Despite significant progress in deep learning for financial trading, existing models often face instability and high uncertainty, hindering their practical application. Leveraging advancements in Large Language Models (LLMs) and multi-agent architectures, we propose a novel framework for quantitative stock investment in portfolio management and alpha mining. Our framework addresses these issues by integrating LLMs to generate diversified alphas and employing a multi-agent approach to dynamically evaluate market conditions. This paper proposes a framework where large language models (LLMs) mine alpha factors from multimodal financial data, ensuring a comprehensive understanding of market dynamics. The first module extracts predictive signals by integrating numerical data, research papers, and visual charts. The second module uses ensemble learning to construct a diverse pool of trading agents with varying risk preferences, enhancing strategy performance through a broader market analysis. In the third module, a dynamic weight-gating mechanism selects and assigns weights to the most relevant agents based on real-time market conditions, enabling the creation of an adaptive and context-aware composite alpha formula. Extensive experiments on the Chinese stock markets demonstrate that this framework significantly outperforms state-of-the-art baselines across multiple financial metrics. The results underscore the efficacy of combining LLM-generated alphas with a multi-agent architecture to achieve superior trading performance and stability. This work highlights the potential of AI-driven approaches in enhancing quantitative investment strategies and sets a new benchmark for integrating advanced machine learning techniques in financial trading can also be applied on diverse markets. </p> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/2412.17712" title="Abstract" id="2412.17712"> arXiv:2412.17712 </a> (replaced) [<a href="/pdf/2412.17712" title="Download PDF" id="pdf-2412.17712" aria-labelledby="pdf-2412.17712">pdf</a>, <a href="/format/2412.17712" title="Other formats" id="oth-2412.17712" aria-labelledby="oth-2412.17712">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Broker-Trader Partial Information Nash-Equilibria </div> <div class='list-authors'><a href="https://arxiv.org/search/q-fin?searchtype=author&query=Wu,+X">Xuchen Wu</a>, <a href="https://arxiv.org/search/q-fin?searchtype=author&query=Jaimungal,+S">Sebastian Jaimungal</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Mathematical Finance (q-fin.MF)</span>; Probability (math.PR); Trading and Market Microstructure (q-fin.TR) </div> <p class='mathjax'> We study partial information Nash equilibrium between a broker and an informed trader. In this setting, the informed trader, who possesses knowledge of a trading signal, trades multiple assets with the broker in a dealer market. Simultaneously, the broker offloads these assets in a lit exchange where their actions impact the asset prices. The broker, however, only observes aggregate prices and cannot distinguish between underlying trends and volatility. Both the broker and the informed trader aim to maximize their penalized expected wealth. Using convex analysis, we characterize the Nash equilibrium and demonstrate its existence and uniqueness. Furthermore, we establish that this equilibrium corresponds to the solution of a nonstandard system of forward-backward stochastic differential equations (FBSDEs) that involves the two differing filtrations. For short enough time horizons, we prove that a unique solution of this system exists. Finally, under quite general assumptions, we show that the solution to the FBSDE system admits a polynomial approximation in the strength of the transient impact to arbitrary order, and prove that the error is controlled. </p> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/2501.05022" title="Abstract" id="2501.05022"> arXiv:2501.05022 </a> (replaced) [<a href="/pdf/2501.05022" title="Download PDF" id="pdf-2501.05022" aria-labelledby="pdf-2501.05022">pdf</a>, <a href="/format/2501.05022" title="Other formats" id="oth-2501.05022" aria-labelledby="oth-2501.05022">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Instrumental Variables Approach to Testing Firm Conduct </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Hong,+Y">Youngjin Hong</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Kim,+I+K">In Kyung Kim</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Kim,+K+i">Kyoo il Kim</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 68 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> Understanding firm conduct is crucial for industrial organization and antitrust policy. In this article, we develop a testing procedure based on the Rivers and Vuong non-nested model selection framework. Unlike existing methods that require estimating the demand and supply system, our approach compares the model fit of two first-stage price regressions. Through an extensive Monte Carlo study, we demonstrate that our test performs comparably to, or outperforms, existing methods in detecting collusion across various collusive scenarios. The results are robust to model misspecification, alternative functional forms for instruments, and data limitations. By simplifying the diagnosis of firm behavior, our method provides an efficient tool for researchers and regulators to assess industry conduct. Additionally, our approach offers a practical guideline for enhancing the strength of BLP-style instruments in demand estimation: once collusion is detected, researchers are advised to incorporate the product characteristics of colluding partners into own-firm instruments while excluding them from other-firm instruments. </p> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/2501.06473" title="Abstract" id="2501.06473"> arXiv:2501.06473 </a> (replaced) [<a href="/pdf/2501.06473" title="Download PDF" id="pdf-2501.06473" aria-labelledby="pdf-2501.06473">pdf</a>, <a href="https://arxiv.org/html/2501.06473v3" title="View HTML" id="html-2501.06473" aria-labelledby="html-2501.06473" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2501.06473" title="Other formats" id="oth-2501.06473" aria-labelledby="oth-2501.06473">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Endogenous Persistence at the Effective Lower Bound </div> <div class='list-authors'><a href="https://arxiv.org/search/econ?searchtype=author&query=Cai,+C">Chunbing Cai</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Roulleau-Pasdeloup,+J">Jordan Roulleau-Pasdeloup</a>, <a href="https://arxiv.org/search/econ?searchtype=author&query=Zheng,+Z">Zhongxi Zheng</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">General Economics (econ.GN)</span> </div> <p class='mathjax'> We develop a perfect foresight method to solve models with an interest rate lower bound constraint that nests OccBin/DynareOBC and \cite{Eggertsson2010}'s as well as \cite{Mertens2014}'s pen and paper solutions as special cases. Our method generalizes the pen-and-paper solutions by allowing for endogenous persistence while maintaining tractability and interpretability. We prove that our method necessarily gives stable multipliers. We use it to solve a New Keynesian model with habit formation and government spending, which we match to expectations data from the Great Recession. We find an output multiplier of government spending close to 1 for the US and Japan. </p> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/2502.13722" title="Abstract" id="2502.13722"> arXiv:2502.13722 </a> (replaced) [<a href="/pdf/2502.13722" title="Download PDF" id="pdf-2502.13722" aria-labelledby="pdf-2502.13722">pdf</a>, <a href="https://arxiv.org/html/2502.13722v2" title="View HTML" id="html-2502.13722" aria-labelledby="html-2502.13722" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2502.13722" title="Other formats" id="oth-2502.13722" aria-labelledby="oth-2502.13722">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Deep Learning for VWAP Execution in Crypto Markets: Beyond the Volume Curve </div> <div class='list-authors'><a href="https://arxiv.org/search/q-fin?searchtype=author&query=Genet,+R">Remi Genet</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistical Finance (q-fin.ST)</span>; Machine Learning (cs.LG) </div> <p class='mathjax'> Volume-Weighted Average Price (VWAP) is arguably the most prevalent benchmark for trade execution as it provides an unbiased standard for comparing performance across market participants. However, achieving VWAP is inherently challenging due to its dependence on two dynamic factors, volumes and prices. Traditional approaches typically focus on forecasting the market's volume curve, an assumption that may hold true under steady conditions but becomes suboptimal in more volatile environments or markets such as cryptocurrency where prediction error margins are higher. In this study, I propose a deep learning framework that directly optimizes the VWAP execution objective by bypassing the intermediate step of volume curve prediction. Leveraging automatic differentiation and custom loss functions, my method calibrates order allocation to minimize VWAP slippage, thereby fully addressing the complexities of the execution problem. My results demonstrate that this direct optimization approach consistently achieves lower VWAP slippage compared to conventional methods, even when utilizing a naive linear model presented in <a href="https://arxiv.org/abs/2410.21448" data-arxiv-id="2410.21448" class="link-https">arXiv:2410.21448</a>. They validate the observation that strategies optimized for VWAP performance tend to diverge from accurate volume curve predictions and thus underscore the advantage of directly modeling the execution objective. This research contributes a more efficient and robust framework for VWAP execution in volatile markets, illustrating the potential of deep learning in complex financial systems where direct objective optimization is crucial. Although my empirical analysis focuses on cryptocurrency markets, the underlying principles of the framework are readily applicable to other asset classes such as equities. </p> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/2503.07498" title="Abstract" id="2503.07498"> arXiv:2503.07498 </a> (replaced) [<a href="/pdf/2503.07498" title="Download PDF" id="pdf-2503.07498" aria-labelledby="pdf-2503.07498">pdf</a>, <a href="https://arxiv.org/html/2503.07498v3" title="View HTML" id="html-2503.07498" aria-labelledby="html-2503.07498" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2503.07498" title="Other formats" id="oth-2503.07498" aria-labelledby="oth-2503.07498">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Diversification and Leverage in a Utility-Based Portfolio Allocation Approach </div> <div class='list-authors'><a href="https://arxiv.org/search/q-fin?searchtype=author&query=Markov,+V">Vladimir Markov</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Section 4 is updated </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Portfolio Management (q-fin.PM)</span>; General Economics (econ.GN) </div> <p class='mathjax'> We examine the problem of optimal portfolio allocation within the framework of utility theory. We apply exponential utility to derive the optimal diversification strategy and logarithmic utility to determine the optimal leverage. We enhance existing methodologies by incorporating compound probability distributions to model the effects of both statistical and non-stationary uncertainties. Additionally, we extend the maximum expected utility objective by including the variance of utility in the objective function, which we term generalized mean-variance. In the case of logarithmic utility, it provides a natural explanation for the half-Kelly criterion, a concept widely used by practitioners. </p> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/2203.04924" title="Abstract" id="2203.04924"> arXiv:2203.04924 </a> (replaced) [<a href="/pdf/2203.04924" title="Download PDF" id="pdf-2203.04924" aria-labelledby="pdf-2203.04924">pdf</a>, <a href="https://arxiv.org/html/2203.04924v2" title="View HTML" id="html-2203.04924" aria-labelledby="html-2203.04924" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2203.04924" title="Other formats" id="oth-2203.04924" aria-labelledby="oth-2203.04924">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Quantum Advantage for Multi-option Portfolio Pricing and Valuation Adjustments </div> <div class='list-authors'><a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Han,+J+Y">Jeong Yu Han</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Cheng,+B">Bin Cheng</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Vu,+D">Dinh-Long Vu</a>, <a href="https://arxiv.org/search/quant-ph?searchtype=author&query=Rebentrost,+P">Patrick Rebentrost</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 42 pages, 1 figure. Comments are welcome </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Quantum Physics (quant-ph)</span>; Computational Finance (q-fin.CP); Mathematical Finance (q-fin.MF) </div> <p class='mathjax'> A critical problem in the financial world deals with the management of risk, from regulatory risk to portfolio risk. Many such problems involve the analysis of securities modelled by complex dynamics that cannot be captured analytically, and hence rely on numerical techniques that simulate the stochastic nature of the underlying variables. These techniques may be computationally difficult or demanding. Hence, improving these methods offers a variety of opportunities for quantum algorithms. In this work, we study the problem of Credit Valuation Adjustments (CVAs) which has significant importance in the valuation of derivative portfolios. As a variant, we also consider the problem of pricing a portfolio of many different financial options. We propose quantum algorithms that accelerate statistical sampling processes to approximate the price of the multi-option portfolio and the CVA under different measures of dispersion. Technically, our algorithms are based on enhancing the quantum Monte Carlo (QMC) algorithms by Montanaro with an unbiased version of quantum amplitude estimation. We analyse the conditions under which we may employ these techniques and demonstrate the application of QMC techniques on CVA approximation when particular bounds for the variance of CVA are known. </p> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/2209.09878" title="Abstract" id="2209.09878"> arXiv:2209.09878 </a> (replaced) [<a href="/pdf/2209.09878" title="Download PDF" id="pdf-2209.09878" aria-labelledby="pdf-2209.09878">pdf</a>, <a href="https://arxiv.org/html/2209.09878v4" title="View HTML" id="html-2209.09878" aria-labelledby="html-2209.09878" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2209.09878" title="Other formats" id="oth-2209.09878" aria-labelledby="oth-2209.09878">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A unifying view on the irreversible investment exercise boundary in a stochastic, time-inhomogeneous capacity expansion problem </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Chiarolla,+M+B">Maria B. Chiarolla</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Optimization and Control (math.OC)</span>; Probability (math.PR); Portfolio Management (q-fin.PM) </div> <p class='mathjax'> This paper devises a way to apply the Bank and El Karoui Representation Theorem to find the investment boundary of a rich stochastic, continuous time capacity expansion problem with irreversible investment on the finite time interval $[0, T]$, despite the presence of a state dependent scrap value associated with the production facility at the terminal time $T$. Standard variational methods are not feasible for the proposed singular stochastic control problem but it admits some first order conditions, complicated however by an extra, non integral term involving the scrap value function and depending on the initial capacity $y$, which are solved by devising a way to apply the Representation Theorem. Such devise, new and of interest in its own right, provides the existence of the base capacity $l^{\star}_y(t)$, a positive level which the optimal investment process is shown to become active at. As far as we know the Representation Theorem has never been applied to this extent. In the special case of deterministic coefficients, under a further assumption specific to the scrap value case, a unifying view on the curve at which it is optimal to invest emerges: the base capacity equals the investment boundary ${\hat y}(t)$ obtained by variational methods. </p> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/2408.11878" title="Abstract" id="2408.11878"> arXiv:2408.11878 </a> (replaced) [<a href="/pdf/2408.11878" title="Download PDF" id="pdf-2408.11878" aria-labelledby="pdf-2408.11878">pdf</a>, <a href="https://arxiv.org/html/2408.11878v2" title="View HTML" id="html-2408.11878" aria-labelledby="html-2408.11878" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/2408.11878" title="Other formats" id="oth-2408.11878" aria-labelledby="oth-2408.11878">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications </div> <div class='list-authors'><a href="https://arxiv.org/search/cs?searchtype=author&query=Huang,+J">Jimin Huang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiao,+M">Mengxi Xiao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+D">Dong Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Jiang,+Z">Zihao Jiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yang,+Y">Yuzhe Yang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+Y">Yifei Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Qian,+L">Lingfei Qian</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+Y">Yan Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Peng,+X">Xueqing Peng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ren,+Y">Yang Ren</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiang,+R">Ruoyu Xiang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+Z">Zhengyu Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Zhang,+X">Xiao Zhang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=He,+Y">Yueru He</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Han,+W">Weiguang Han</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Chen,+S">Shunian Chen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Shen,+L">Lihang Shen</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Kim,+D">Daniel Kim</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+Y">Yangyang Yu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Cao,+Y">Yupeng Cao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Deng,+Z">Zhiyang Deng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Li,+H">Haohang Li</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Feng,+D">Duanyu Feng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Dai,+Y">Yongfu Dai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Somasundaram,+V">VijayaSai Somasundaram</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lu,+P">Peng Lu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xiong,+G">Guojun Xiong</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+Z">Zhiwei Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Luo,+Z">Zheheng Luo</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yao,+Z">Zhiyuan Yao</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Weng,+R">Ruey-Ling Weng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Qiu,+M">Meikang Qiu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Smith,+K+E">Kaleb E Smith</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Yu,+H">Honghai Yu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lai,+Y">Yanzhao Lai</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Peng,+M">Min Peng</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Nie,+J">Jian-Yun Nie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Suchow,+J+W">Jordan W. Suchow</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Liu,+X">Xiao-Yang Liu</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Wang,+B">Benyou Wang</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lopez-Lira,+A">Alejandro Lopez-Lira</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Xie,+Q">Qianqian Xie</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Ananiadou,+S">Sophia Ananiadou</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Tsujii,+J">Junichi Tsujii</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 33 pages, 13 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation and Language (cs.CL)</span>; Computational Engineering, Finance, and Science (cs.CE); Computational Finance (q-fin.CP) </div> <p class='mathjax'> Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow evaluations, making them less suited for real-world application. To address this, we introduce \textit{Open-FinLLMs}, the first open-source multimodal financial LLMs designed to handle diverse tasks across text, tabular, time-series, and chart data, excelling in zero-shot, few-shot, and fine-tuning settings. The suite includes FinLLaMA, pre-trained on a comprehensive 52-billion-token corpus; FinLLaMA-Instruct, fine-tuned with 573K financial instructions; and FinLLaVA, enhanced with 1.43M multimodal tuning pairs for strong cross-modal reasoning. We comprehensively evaluate Open-FinLLMs across 14 financial tasks, 30 datasets, and 4 multimodal tasks in zero-shot, few-shot, and supervised fine-tuning settings, introducing two new multimodal evaluation datasets. Our results show that Open-FinLLMs outperforms afvanced financial and general LLMs such as GPT-4, across financial NLP, decision-making, and multi-modal tasks, highlighting their potential to tackle real-world challenges. To foster innovation and collaboration across academia and industry, we release all codes (<a href="https://anonymous.4open.science/r/PIXIU2-0D70/B1D7/LICENSE" rel="external noopener nofollow" class="link-external link-https">this https URL</a>) and models under OSI-approved licenses. </p> </div> </dd> </dl> <div class='paging'>Total of 19 entries </div> <div class='morefewer'>Showing up to 2000 entries per page: <a href=/list/q-fin/new?skip=0&show=1000 rel="nofollow"> fewer</a> | <span style="color: #454545">more</span> | <span style="color: #454545">all</span> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; line-height: 2;"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul style="list-style: none; 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