This paper investigates whether stocks earn a premium for their sensitivity to market tail events, referred to as tail risk exposure (TRE). We show that commonly used estimators of TRE, typically based on tail dependence between asset and market returns exhibit significant statistical biases, particularly in the presence of general market dependence. Empirically, we find that tail risk is priced only in low-correlation stocks, where average market comovement is weak. This suggests that investors underestimate TRE in low-correlation stocks and overestimate it in high-correlation stocks. To address this, we propose a novel double-sort portfolio strategy that accounts for both TRE and correlation, allowing us to isolate and accurately price TRE. This strategy consistently outperforms traditional single-sort methods in terms of predictive accuracy and risk-adjusted returns.

We develop a satisficing model of choice in which the available alternatives differ in their inherent complexity. We assume—and experimentally validate—that complexity leads to errors in the perception of alternatives’ values. The model yields sharp predictions about the effect of complexity on choice probabilities, some of which qualitatively contrast with those of maximization-based choice models. We confirm the predictions of the satisficing model—and thus reject maximization—in a novel data set with information on hundreds of millions of real-world chess moves by highly experienced players. Looking beyond chess, our work offers a blueprint for incorporating complexity at the level of individual objects into models of choice and for detecting satisficing outside of the laboratory.

We examine whether PCAOB inspection deficiencies related to management review controls (MRCs) affect financial reporting decisions. Using the goodwill impairment setting, we find that firms are more likely to record goodwill impairments when their auditors have received more PCAOB inspection deficiencies related to goodwill MRCs. The association is stronger when inspection deficiencies are more likely to lead to changes to the design or implementation of an internal control (repeat deficiencies and deficiencies related to MRC precision). We observe some evidence that MRC inspection deficiencies increase the likelihood of goodwill impairment even when unrelated to goodwill, indicating that improving the audit of MRCs can broadly affect financial reporting. Our findings provide evidence that PCAOB inspections affect not only auditor behavior but also the financial reporting behavior of audit clients. Specifically, inspection feedback appears to influence reporting outcomes through changes in the audit and evaluation of MRCs, identifying a channel through which regulatory oversight affects issuers. The results have implications for audit firms seeking to remediate inspection deficiencies, for management and audit committees responsible for overseeing significant estimates and impairment analyses, and for regulators evaluating the broader effectiveness of the PCAOB inspection process.

Mandatory audits of internal controls over financial reporting (ICFR), intended to strengthen financial reporting processes, may also have implications for broader organizational compliance systems. Increased scrutiny of financial controls could either enhance overall control quality, yielding benefits for nonfinancial controls, or induce firms to reallocate resources away from those areas. We exploit quasi‐exogenous variation in financial control scrutiny arising from (1) the initial implementation of ICFR audits, (2) the subsequent relaxation of ICFR auditing standards, and (3) the introduction of management assessments of financial controls absent concurrent ICFR audits, to examine how changes in external scrutiny affect Food and Drug Administration (FDA) inspection findings, an important form of regulatory noncompliance with direct public health implications. Our results show that the introduction of ICFR audits is associated with a reduction in FDA inspection findings; however, these benefits reverse when ICFR audit scrutiny declines. Mechanism analyses suggest that remediation of control deficiencies, investments in information systems, and expanded internal audit functions facilitate spillovers to compliance controls. Importantly, we find limited evidence that management assessments alone, without concurrent ICFR audits, generate similar spillover effects. Overall, our findings suggest that internal control systems operate as integrated organizational processes rather than isolated financial reporting mechanisms and that external scrutiny plays a critical role in enabling spillovers across control domains. These insights have implications for audit committees, auditors, regulators, and other stakeholders.

Gun violence is a major problem in the United States, and extensive prior work has shown that higher temperatures increase violent behavior. We consider whether restricting the concealed carry of firearms mitigates or exacerbates the effect of temperature on violence. We use two identification strategies that exploit daily variation in temperature and variation in gun control policies between and within states. We provide evidence that more-prohibitive concealed-carry laws attenuate the temperature-homicide relationship. Our findings are consistent with more-prohibitive policy regimes reducing the lethality of altercations.

The digital evolution in auditing has triggered a rapid shift in auditors' required skill sets, with audit firms heavily investing in and extolling advanced data analytics and artificial intelligence (AI) capabilities. However, this strong emphasis on newly required digital skills can lead many experienced auditors, who perceive these competencies as their weaker areas, to feel disaffirmed in their abilities. We predict and find, across two experiments, that auditors who feel disaffirmed in their digital skills more defensively discount specialist advice that places higher versus lower reliance on AI, but that an intervention in which auditors affirm their traditional audit skills mitigates this defensive reaction. Absent self‐affirmation, higher specialist reliance on AI results in auditors denigrating the competence and quality of advice that specialists provide. These findings suggest that disaffirmation escalates AI aversion, offering important insights into how audit firms can foster less defensive decision‐making in the rapidly evolving audit environment.

Using sales and leasing data, this paper finds three novel effects of a higher property transaction tax: higher buy-to-rent transactions alongside lower buy-to-own transactions despite both being taxed, a lower sales-to-leases ratio, and a lower price-to-rent ratio. This paper explains these facts by developing a search model with entry of investors and households, households choosing to own or rent in the presence of credit frictions, and homeowners deciding when to move house. A higher transaction tax reduces homeowners’ mobility and increases demand for rental properties, which explains the empirical facts and leads to a lower homeownership rate. The deadweight loss is large at 111% of tax revenue, with more than half of this due to distorting decisions to own or rent.

We show that leading investor disagreement proxies have near-zero cross-correlation – making disagreement pricing inferences challenging. We develop a frictionless model that generates overpricing from latent disagreement, jointly rationalizes major proxies, and generates new testable predictions. Equilibrium interrelationships motivate a new disagreement measure, DIS, which is more predictive of returns cross-sectionally than major proxies and more consistently predictive across macroeconomic regimes. We provide evidence that the friction-based channel of Miller (1977) and a frictionless mechanism coexist and are empirically separable. DIS also provides a micro-founded, disagreement-based account of the IVOL puzzle, absorbing IVOL’s predictability while revealing its regime and friction dependence.

We develop a model-free measure of the variance premium by constructing option portfolios whose returns are highly correlated with realized stock variance. This effectively decomposes returns into realized variance minus implied variance. We apply this decomposition to document a novel quarterly cross-sectional continuation pattern in both realized variance and implied variance of individual stocks. Implied variance underanticipates the seasonality of realized variance, so options that performed well at quarterly lags continue to earn high returns in the future. Quarterly periodicity in realized stock variance only occurs on days with analyst earning revisions, suggesting an informational channel for this pattern.

Using a novel measure of investment companies’ reliance on generative artificial intelligence (GenAI), we document a sharp increase in GenAI usage by hedge funds after ChatGPT’s 2022 launch. A difference-in-differences test shows that hedge funds adopting GenAI earn 2-4% higher annualized abnormal returns than nonadopters, while non-hedge funds do not benefit. The outperformance originates from funds’ AI talent and ChatGPT’s strength in analyzing firm-specific information. We conduct a new survey of fund managers’ GenAI usage to provide direct validation of our measure and offer additional new insights on how managers adopt GenAI tools in their practice.