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Is Informed Short Selling Concentrated in Family Firms? Evidence from a Reinvestigation

Journal of Finance 2026
We reinvestigate Anderson, Reeb, and Zhao's findings that informed short selling is unique to family firms and driven by information leakage from internal disputes. Using the same firm sample and more comprehensive short‐selling data, we find that short selling predicts future returns in both family and nonfamily firms. We also find no significant difference in abnormal short selling before negative earnings announcements. In extended sample periods, short selling continues to predict returns for nonfamily firms under both ownership‐based and familial‐link definitions. Overall, our evidence suggests that short sellers are broadly informed and that family firms are not uniquely vulnerable.

Housing Yields

Journal of Financial and Quantitative Analysis 2026
We build a granular data set of residential property yields using rental and sale listings from a major German real estate platform. With more than 1.5 million property-level rent-to-price ratios, we document a novel heterogeneity puzzle. About two-fifths of yield dispersion remains unexplained after controlling for extensive observable property characteristics and postal code-level time-varying factors using fixed effects. When we absorb finer neighborhood amenities through richer fixed effects, the unexplained share remains close to one-third. This evidence points to the importance of investors’ beliefs and preferences—rather than several alternative explanations we test—as sources of heterogeneity in risk premia.

Economic Fundamentals and Short-Run Exchange Rate Prediction: A Machine-Learning Perspective

Journal of Financial and Quantitative Analysis 2026
The exchange rate predictability puzzle—that fundamentals fail to forecast short-horizon exchange rate movements out of sample—has long resisted resolution. We show that fundamentals do matter, but their effects vary with global financial conditions. Using a rich set of country characteristics interacted with global state variables and machine-learning techniques to handle the high-dimensional data, we document that interactions between country characteristics and foreign exchange market volatility are particularly important, consistent with a “flight to fundamentals” during periods of financial stress. Our forecasts deliver substantial economic value and offer new insight into the carry trade.