Knowledge that Transforms

Conventionally, it is very difficult to differentiate factor risk premium from mispricing. Motivated by the fact that short-sellers take advantage of observable mispricing, this paper highlights the different effects of short selling activity on the profitability and investment premia. We find that the profitability premium disappears among the stocks with high short selling activity whereas short selling has no impact on the investment premium. We also show that the profitability premium is more likely than the investment premium to be associated with the sentiment-driven mispricing, which is eliminated among heavily shorted stocks. Collectively, our results suggest that the two new premia have different underlying attributions. While the profitability premium is more consistent with the mispricing interpretation, the investment premium is not.

This paper develops and tests an equilibrium model of active fund management with ESG considerations. Heterogeneous sustainability preferences lead fund managers to intensify information acquisition on assets across the ESG spectrum, broadening the scope of active management. This information channel enhances price informativeness, lowers discount rates, and increases portfolio deviation from benchmarks. The model predicts a negative and concave ESG-expected return relation, stronger for green assets and weaker for brown assets. Using data on U.S. mutual funds and stocks from 2007–2021, we find supporting evidence based on price informativeness and the implied cost of equity capital.

Our primary contribution to the finance literature is the introduction of folklore narratives as a major factor in influencing corporate outcomes. Using the initial public offering (IPO) underpricing as the main focus, we demonstrate that folklore narratives depicting lower tolerance toward antisocial behavior are associated with lower IPO underpricing. The relation between folklore narratives and IPO pricing is independent of indicators of trust, religion, culture, societal preferences, or institutional democracy. This relation is weaker in countries with a more transparent information environment and following reforms that improve disclosure and corporate governance. Folklore narratives on punishment for antisocial behavior are also related to enhanced information disclosure, lower agency problems, better long-term performance for IPO firms, higher proceeds raised and free float, and overall IPO activity in the market. Collectively, we show that informal institutions, such as folklore narratives, exert a strong influence on IPO outcomes globally.

We examine the role of methodological uncertainty in studies of international variation in country equity returns, analyzing 15 predictors across 69,120 unique research designs. By varying ten key methodological decisions-spanning data sources, sample preparation, and portfolio implementation-we reveal substantial differences in results. Many established patterns like momentum and valuation effects prove surprisingly fragile. Research designs emphasizing small, segmented markets imrove observed performance, while those focusing on more liquid and accessible peers diminish returns. Using a bootstrap-based test, we identify only a few robust factors, such as market size, issuance, and political risk. Our findings highlight the need for methodological transparency in future research.

<div> We propose option realized semivariances and signed jumps as new “observable quantities” to summarize the asymmetric information contained in the sign of high-frequency option returns. These measures successfully capture the direction of the discontinuities related to both the underlying asset and risk factor, yielding incremental information not contained in the aggregate option realized measures. Using options data on S&P 500 ETF (SPY) and 15 individual equities, we document that the negative (positive) semivariance and signed jump of out-of-the-money call (put) options play a prominent role in predicting future variance, variance risk-premia, and excess monthly returns. Out-of-sample volatility timing strategies based on these measures generate economically significant gains of up to 206 basis points annually for risk-averse investors. </div>

Conventional wisdom holds that a common currency deprives countries of an important tool for responding to domestic shocks. This paper explores the extent to which a common currency can also facilitate cross-country risk sharing. I develop a monetary model in which asymmetric productivity shocks are partly smoothed through terms-of-trade adjustment and current account imbalances. When these adjustments are incomplete, the central bank can further promote risk sharing by refinancing current account imbalances through an uneven allocation of liquidity across countries. For moderate shocks, this redistribution does not interfere with the inflation target, while large asymmetric shocks create a trade-off between risk sharing and inflation. Applying the model to the 2008–2012 Eurocrisis, I document substantial central-bank-mediated financing of current account imbalances. I find that the common currency channel absorbed roughly one quarter of country-specific output shocks at a time when private markets and fiscal risk-sharing mechanisms were impaired.

This paper reexamines the beta-return relation through the lens of time-varying risk aversion. We show that the security market line (SML) depends critically on the level of aggregate risk aversion. During periods of high risk aversion, the SML exhibits a positive slope and an intercept that is statistically indistinguishable from zero, with investor sentiment playing only a minor role. During periods of low risk aversion, the SML slope becomes negative and the intercept is significantly positive. Investor sentiment affects the SML only when risk aversion is low. These patterns are robust across alternative portfolio constructions, longer investment horizons, and multiple measures of risk aversion.

Despite the growing integration of artificial intelligence (AI) into business models, studies of its impact on corporate climate change exposure remain scarce. Through an examination of AI-related innovations among US-listed firms from 2001 to 2019, we present compelling evidence that AI innovation effectively mitigates firms’ climate change exposure. In particular, it reduces firms’ exposure to regulatory and physical risks related to climate change through improved carbon management efficiency, with computer vision and control and planning being the most effective types in this context. Our findings are particularly pronounced for mature firms and those facing greater regulatory intervention. The results withstand rigorous tests that address endogeneity concerns. Our study provides strong support for firms to adopt AI innovations to achieve carbon neutrality, contributing to the ongoing discourse regarding AI trade-offs. Our findings also offer valuable insights into the development of climate risk mitigation strategies.