Knowledge that Transforms

Abstract We propose a novel trend factor for the Chinese stock market that incorporates both price and volume information to capture dominant individual trading, momentum, and liquidity. We find that volume plays a more significant role in the trend factor for China than for the United States, reflecting the greater retail participation in China. By incorporating this trend factor into the 3-factor model of Liu et al. (2019), we propose a 4-factor model that explains a wide range of stylized facts and 60 representative anomalies. Our study highlights the important role of individual trading in asset pricing, especially in China. (JEL G12, G14, G15)

Abstract We provide evidence that equity investors are slow to process information about how current oil price changes affect future earnings announcements. Stock prices respond to lagged quarterly oil price changes when firms start announcing earnings in the next quarter. A cross-sectional equity trading strategy that exploits this predictability yields an annualized Sharpe ratio of 0.50. Our oil-response forecast strategy earns especially high returns after large absolute oil price changes, in recessions or bear markets, and during peak earnings season. The predictability we document is consistent with limited attention, is not driven by risk factor exposure, and survives several robustness tests. (JEL G10, G11, G14, G40, Q41)

Abstract This paper investigates the influence of global equity market value shocks on institutional investors’ (IIs’) hedging behavior and the resultant effects on exchange rates. Employing unique granular daily data on Israeli IIs’ foreign exchange (FX) forward flows and prices and a granular instrumental variable estimation approach, we find that foreign equity market value shocks generate significant selling of U.S. dollar forwards by IIs, as a hedge against heightened FX exposure, along with significant exchange rate appreciation. A value-shock-induced one-standard-deviation increase in IIs’ supply of forward flows appreciates IIs’ forward rate by 0.53%. (JEL E44, F3, F31, G15, G23)

Abstract In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of both predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance. (JEL G10, G11, C52, C55)

Abstract This paper studies the extent to which macro-finance term structure models are susceptible to predictive uncertainty. We propose a general form of arbitrage-free models and quantify the relative importance of unpredictable priced risk variance, as well as macro-finance model uncertainty and learning uncertainty in predictability. Predictive performance and relative contributions of uncertainty sources are dynamically measured based on Bayesian methods, revealing dominating priced risk variance and other important uncertainty sources at different points in time. Macro-finance model uncertainty is high for near-term forward spread forecasts and contributes up to 87% of predictive uncertainty prior to recessions, implying strong dispersion in the information content of macro variables when forming near-term monetary policy expectations. (JEL C1, C3, C5, D8, E4, G1)

Abstract We implement a dynamically regularized, bootstrapped two-stage out-of-sample parametric portfolio policy to evaluate characteristics’ efficacy in the conditional stock return-generating process in the metric of expected power utility. Traditional characteristics, such as momentum and size afforded large utility gains before 1999. These opportunities have since vanished. Overfitting—imprecision in weight estimation—is correlated with the optimal portfolio’s variance. Therefore, it is not a problem for power utility investors with coefficients of relative aversion greater than four. For more risk-tolerant investors, we successfully reduce estimation error by increasing the curvature of the loss function relative to the investor’s utility function. (JEL L200; C110; C350)

Abstract This paper revisits the relation between systematic skewness and returns, showing two main findings. First, the systematic skewness premium in individual stocks is time varying. When either skewness preference or systematic skewness is above rather than below the median, the premium is 4% higher. The combined effect of the two induces time variation in the premium of about 7%. Second, systematic skewness has significant additional explanatory power in explaining returns relative to most common characteristics, except size and momentum. These two results imply that skewness preference is an important determinant of expected returns providing a possible rationale for size and momentum. (JEL G11, G12)

Abstract We explore the impact of investors’ beliefs on cryptocurrency demand and prices using new individual-level survey data and a structural characteristics-based demand model with differentiated cryptocurrencies and heterogeneous investors. We show that younger individuals with lower incomes are more optimistic about the future value of cryptocurrencies, as are late investors. We identify the model combining observable beliefs with an instrumental variable strategy that exploits variation in the production of different cryptocurrencies. Counterfactual analyses quantify the impact on portfolio allocations and equilibrium prices of (i) (regulating) entry of late optimistic investors, and (ii) growing concerns among investors about the sustainability of energy-intensive proof-of-work cryptocurrencies. (JEL: D84, G11, G41)

Abstract This paper highlights a positive and significant beta-return relationship in high expected market return states, as suggested by the ICAPM. The ICAPM has strong out-of-sample predictive power for equity returns. As a result, timing strategies exploiting this predictive power have Sharpe ratios about double those of the buy-and-hold strategies, alphas of about 5% per annum, and average returns increasing sharply with unconditional betas. Our findings relate to the positive beta-return relation uncovered overnight, on macroeconomic announcement days, and in low inflation times because these periods share an important common feature: high market returns. (JEL D53, G11, G12)

Abstract Regulations introduce significant fixed costs and add to operating leverage. Fixed regulatory costs that contribute to operating leverage should generate a risk premium. To explore whether such a premium exists, we introduce a measure of “regulatory operating leverage” that reflects the importance of fixed regulatory costs in a firm’s cost structure. Regulatory operating leverage predicts stock returns in the cross-section, and a zero-cost high-low regulatory operating leverage strategy generates positive and significant risk-adjusted return. Finally, the impact of regulatory operating leverage on returns is due to the (systematic) risk contribution of fixed regulatory costs.