Journal of Empirical Finance最新文献

Using publicly available information on option volume totals, we develop new measures of directional option-to-stock (O/S) trading volume imbalance. The novel measures are strongly related to the cash-flow (CF) and discount-rate (DR) news components of unexpected stock returns and consistently predict future abnormal performance. While options markets respond more strongly to CF news than do equity markets, they still do not fully incorporate CF news into prices and therefore lead to returns predictability. This underreaction phenomenon is of smaller magnitude when the options market response is stronger and when short-sale constraints are less binding.

This paper investigates high-dimensional factor models for cross-sectional asset returns, with a specific focus on robust estimation in the presence of (highly) correlated factors. Factor correlations can significantly compromise the robustness and credibility of commonly employed analytical methods. To address this, we utilize the stochastic discount factor (SDF) and integrate it with a recently developed Machine Learning methodology (Figueiredo and Nowak, 2016). This novel approach allows us to select factors while accounting for factor correlations and to disentangle correlated factors without imposing rigid assumptions. Our empirical findings consistently highlight the paramount role of the ‘market’ factor in driving cross-sectional asset returns. In contrast, other benchmarks, including the LASSO, the Elastic-Net, and the Fama–MacBeth regression, are adversely impacted by factor correlations, rendering the ‘market’ factor redundant. Additionally, our findings underscore the importance of ‘profitability’, ‘momentum’, and ‘liquidity’-related factors in driving cross-sectional asset returns.

Important portfolio choice decisions are made for large groups of heterogeneous individual investors. I propose solving the cross-sectional average of the individual Euler equations to find an optimal portfolio for an aggregate of investors under one-size-fits-all constraints. Using a dynamic portfolio choice model to design balanced default funds for 72 hypothetical industry pension plans, the average Euler equations depend on industry-specific per-capita earnings growth and moments of idiosyncratic earnings shocks. Inter-industry heterogeneity in moments of the joint distribution of earnings growth and the return on risky assets, including correlation and cokurtosis, explains the variation in optimal choice variables across industries.

Using audit trail data from the Taiwan Stock Exchange, this paper compares the trading skill of institutions and individuals around information shocks. We find suggestive evidence that institutions possess information acquisition and processing advantages over individuals. Specifically, net buying done by institutions (individuals) prior to and during jumps positively (negatively) predicts future intraday returns. This predictive relation is strongest among stocks with high limits to arbitrage and a limited information environment. Moreover, domestic institutions generate higher trading profits than foreign institutions. Unlike domestic institutions, the information acquisition and processing advantages of foreign institutions prevail across different sources of price jumps, such as prescheduled events and macroeconomic news. Prescheduled events and news lessen the information disadvantages for individuals.

How do commercial banks react to natural disasters? Using data for 375 droughts in 262 prefectures in China during 1906–1927, we find that drought-affected prefectures have more private bank inceptions than unaffected ones. The results remain robust to socioeconomic characteristics, foreign market exposure, and conditions of neighboring prefectures. This effect is driven by the prefectures with more agriculture-dependent enterprises, suggesting that banks meet local financial demand. On the other hand, new banks would enter less when the prefecture has more incumbent banks connected to drought-free areas. We argue that capital size and the network of capital reallocation are two advantages of banks coping with natural disasters over alternative financing vehicles such as pawn shops and foreign banks. In addition, the effect is greater among the prefectures practicing common law and with greater social capital, consistent with existing studies that bank credit supply depends on creditor rights protection. Finally, we show that drought-affected regions with more private bank inceptions have better development in agricultural businesses and social stability.

Motivated by the present-value framework, this article proposes a novel and flexible semiparametric long-horizon time-varying model to investigate the so-called ‘pockets of predictability’, which refer to local periods in which stock returns or cash flows are significantly predictable. A semiparametric profile method is used to estimate both time-varying and constant parameters. In the empirical studies, the predictive ability of the dividend-price ratio for dividend growth is considerably weaker than its ability to predict stock returns at both short and long horizons. Moreover, dividend smoothing only matters for dividend growth predictability at a low frequency. In addition, localized variance decomposition analysis suggests that the present-value relation is locally valid for most sample periods and that the main driver of the variation in the dividend-price ratio stems from its ability to predict stock returns. Lastly, using the earnings-price ratio produces similar results.

This paper proposes a new way of estimating the instantaneous volatility of fixed income securities using derivatives data, which can further be used to construct the corresponding yield curve variance risk premium (VRP). We show that this VRP measure exhibits strong long-horizon predictive power for bond excess returns. After controlling for the shape of the yield curve, the VRP strongly predicts 1-year holding period excess returns for 2-year to 10-year zero coupon bonds. The marginal $R^2$ of VRP is as high as 12.6%. One standard deviation increase in the VRP is associated with 2.224% increase in the bond excess return. This result is robust when we include various other bond return predictors, such as the Cochrane–Piazzesi “tent-shaped” factor. The out-of-sample analysis suggests that this predictability is not only statistically significant, but also can be translated into economic gains. Additional tests suggest that this predictability varies with economic conditions.

Consistent with models of intermediaries who absorb demand pressure from end-users and respond by changing prices, net option demand is positively related to option prices in the market for VIX puts and calls. VIX and SPX option markets are integrated: market-makers absorb end-users’ net long volatility positions and net demand affects prices across markets. Net demand changes in the most liquid markets result in spillover effects between the VIX and SPX markets. A dynamic characterization of prices and net demand suggests that VIX option markets and the SPX put market are integrated, while the SPX call market is more segregated.

This paper studies whether all-star females’ representation in brokerages leads to positive outcomes. I find that an increase in the number of all-star females in a brokerage spurs the future performance of other analysts in that brokerage. Knowledge spillover is an economic channel that explains this effect, as analysts who cover firms in the same industry as all-star females experience a larger boost in their outcomes. A higher representation of all-star females in a brokerage further improves the timeliness of other analysts’ forecasts. Overall, the results suggest that all-star female analysts have a positive effect on the outcome of their workplace.

Volatility clustering, widely observed in daily equity market returns, has not been analyzed for high-resolution intraday and overnight returns, nor has its time scale dependency been systematically explored. This paper examines the volatility clustering of intraday and overnight returns in 15 global equity markets, both developed and emerging. Findings reveal universal volatility clustering in intraday and overnight returns across various time scales, from daily to monthly and beyond. It appears that the volatility clustering of overnight returns is even more pronounced than intraday returns. However, the cross clustering between two volatility series is generally weak within each market. These observations suggest both short- and long-term investment risks, providing meaningful insights for equity market investors’ risk management.