Long-term investment strategies suited for large institutional investors.
Stocks tend to perform better in the same calendar months they did well in the past. This paper shows that historical same-month returns are strong predictors of future performance—across stocks, anomalies, industries, countries, and even commodities.
Analysts often issue optimistic return forecasts and recommendations that directly contradict well-documented anomaly signals. This paper shows that anomaly-longs are underappreciated and anomaly-shorts are overhyped—despite the anomalies' proven predictive power.
This paper shows that when an anomaly becomes widely known (i.e., "discovered"), arbitrageurs begin exploiting it—reducing its future returns, changing correlations, and indirectly benefiting passive investors through diversification.
This paper finds that stock return anomalies—long known to be profitable—perform much better on days with firm-specific news. Anomalies earn 50% higher returns on news days and over 6× more on earnings days, suggesting these effects are driven by investor misbeliefs corrected when news arrives.
This paper shows that timing factor exposures over time can improve performance significantly. By forecasting returns on key equity anomalies using valuation signals, the authors build a dynamic portfolio that earns higher Sharpe ratios than static factor investing or market timing alone.
This paper shows that investors with limited ability to borrow tend to chase high-risk assets. As a result, low-risk (low-beta) assets offer better risk-adjusted returns. A strategy that goes long low-beta assets and shorts high-beta ones—called “Betting Against Beta”—consistently beats the market.
High-frequency traders (HFTs) often compete with large institutional trades, raising execution costs for informed orders. This paper shows that when HFT speed is restricted, price impact drops—especially for skilled institutional traders.
Macroeconomic uncertainty isn’t just noise—it reshapes bond risk premia and pricing.
This paper shows that the part of the variance risk premium tied to downside tail risk—jumps in asset prices—is what really predicts market returns. It's a cleaner measure of investor fear than the VIX.
It’s not volatility, but the anticipation of risk that drives returns. This paper shows how timing macro events reveals the hidden premium of uncertainty.
Bitcoin’s extreme volatility comes with an upside: low correlation with other assets. This paper shows that even a small allocation to Bitcoin can significantly boost the Sharpe ratio of a diversified portfolio.
During financial crises, hedge funds and commodity index traders (CITs) offload positions as volatility rises, forcing commercial hedgers to absorb risk. This “risk convection” disrupts markets, creating trading opportunities based on liquidity shifts.