This paper documents a significantly negative cross-sectional relation between left-tail risk and future returns on individual stocks trading in the U.S. and international countries. We provide a behavioral explanation to this anomaly based on the idea that investors underestimate the...

Frazzini and Pedersen (2014) document that a betting against beta strategy that takes long positions in low-beta stocks and short positions in high-beta stocks generates a large abnormal return of 6.6% per year and they attribute this phenomenon to funding liquidity risk. We demonstrate that...

This paper reexamines the relation between various downside risk measures and future equity returns in a global context that spans 26 developed markets. We find that there is no significantly positive relation between systematic downside risk and the cross-section of equity returns, and in fact,...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

Hedge funds' extensive use of derivatives, short-selling, and leverage and their dynamic trading strategies create significant non-normalities in their return distributions. Hence, the traditional performance measures fail to provide an accurate characterization of the relative strength of hedge...

Hedge funds' extensive use of derivatives, short-selling, and leverage and their dynamic trading strategies create significant non-normalities in their return distributions. Hence, the traditional performance measures fail to provide an accurate characterization of the relative strength of hedge...

Contrary to the theoretical principle that higher risk is compensated with higher expected return, the literature shows that low-risk stocks outperform high-risk stocks. Using a large-scale household dataset, we provide an explanation for this puzzling result that the anomalous negative...

We propose a belief-generating model from which we build a statistical measure of investor disagreement. We simulate differences in beliefs across investors by endowing them with different machine learning models for forecasting returns from the same set of inputs. We measure disagreement as the...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

This paper investigates hedge funds' ability to time industry-specific returns and shows that funds' timing ability in the manufacturing industry improves their future performance, probability of survival, and ability to attract more capital. The results indicate that best industry-timing hedge...