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作者：Han, Xia; Lin, Liyuan; Wang, Ruodu
作者单位：Nankai University; Nankai University; Monash University; University of Waterloo
摘要：We establish the first axiomatic theory for diversification indices using six intuitive axioms: nonnegativity, location invariance, scale invariance, rationality, normalization, and continuity. The unique class of indices satisfying these axioms, called the diversification quotients (DQs), are defined based on a parametric family of risk measures. A further axiom of portfolio convexity pins down DQs based on coherent risk measures. The DQ has many attractive properties, and it can address seve...
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作者：Voleti, Sudhir; Malladi, Vishwakant; Sohoni, Milind G.
作者单位：Indian School of Business (ISB); State University of New York (SUNY) System; University at Buffalo, SUNY
摘要：We investigate whether and to what extent financial markets value and respond to operations management (OM)-related information in quarterly earnings calls directed toward financial market participants. We develop and use a novel construct called stated OM focus (SOMF) to mine the incidence of and emphasis on OM information in the quarterly earnings conference calls for a large cross-section of firms (S&P 1500) over a time frame of 15 years. We empirically establish the value-relevance of OM i...
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作者：Fereidouni, Meysam; Nault, Barrie R.
作者单位：Simon Fraser University; University of Calgary
摘要：Despite utilizing technical prevention methods and enacting copyright protection legislation, digital piracy has remained a persistent problem. We examine policy remedies to digital piracy whereby the policymaker has to balance its budget between fines on detected pirates, subsidies for legal purchases, and restitution to the firm. In our model, users choose whether to subscribe, copy, or not use the good, a firm decides on subscription fee and quality, and a policymaker determines subsidies, ...
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作者：Loch, Christoph
作者单位：University of Navarra
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作者：Aleti, Saketh; Bollerslev, Tim; Siggaard, Mathias
作者单位：Duke University; CREATES; Aarhus University
摘要：We provide strong empirical evidence for time-series predictability of the intraday return on the aggregate market portfolio by exploiting lagged high-frequency crosssectional returns on the factor zoo. Our results rely on the use of modern machine-learning techniques to regularize the predictive regressions and help tame the signals stemming from the zoo together with techniques from financial econometrics to differentiate between continuous and theoretically nonpredictable discontinuous high...
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作者：de Kok, Ties
作者单位：University of Washington; University of Washington Seattle
摘要：Generative large language models (GLLMs), such as ChatGPT and GPT-4 by OpenAI, are emerging as powerful tools for textual analysis tasks in accounting research. GLLMs can solve any textual analysis task solvable using nongenerative methods as well as tasks previously only solvable using human coding. Whereas GLLMs are new and powerful, they also come with limitations and present new challenges that require care and due diligence. This paper highlights the applications of GLLMs for accounting r...
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作者：Gaertner, Fabio B.; Hoopes, Jeffrey L.; Kelley, Stacie O.; Pflitsch, Max
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Dortmund University of Technology
摘要：The Inflation Reduction Act establishes a new 15% corporate minimum tax on the adjusted financial accounting income for large U.S. corporations. Although the minimum tax is estimated to raise $222 billion over 10 years, some fear firms will manipulate their accounting earnings to reduce their tax liabilities, resulting in less revenue raised. Using an event study, we examine the extent to which investors believe this tax will reduce firm value. We examine stock market reactions around key legi...
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作者：Xu, Kan; Bastani, Hamsa
作者单位：Arizona State University; Arizona State University-Tempe; University of Pennsylvania
摘要：Decision makers often simultaneously face many related but heterogeneous learning problems. For instance, a large retailer may wish to learn product demand at different stores to solve pricing or inventory problems, making it desirable to learn jointly for stores serving similar customers; alternatively, a hospital network may wish to learn patient risk at different providers to allocate personalized interventions, making it desirable to learn jointly for hospitals serving similar patient popu...
