We propose a new class of performance measures for Hedge Fund (HF) returns based on a family of empirically identifiable stochastic discount factors (SDFs). The SDF-based measures incorporate no-arbitrage pricing restrictions and naturally embed information about higher-order mixed moments...

We develop a new approach to evaluate asset pricing models (APMs) based on Minimum Discrepancy (MD) projections that generalize the Hansen-Jagannathan (HJ, 1997) distance to account for an arbitrary number of moments of asset returns. The Minimum Discrepancy projections correct APMs to become...

We combine high-frequency stock returns with risk-neutralization to extract the daily common component of tail risks perceived by investors in the cross-section of firms. We find that our tail risk measure significantly predicts the equity premium, variance risk premium and realized moments of...

This paper introduces a new tail risk measure based on the risk-neutral excess expected shortfall of a cross-section of stock returns. We propose a novel way to risk neutralize the returns without relying on option price information. Empirically, we illustrate our methodology by estimating a...

This paper proposes to extract tail risk from a risk-neutral mean-adjusted expected shortfall of high-frequency stock returns. Risk adjustment is based on a nonparametric estimator of the state price density that does not use option prices and relies solely on a stock index returns. This makes...

Hansen and Jagannathan (1997) compare misspecified asset pricing models based on least-square projections on a family of admissible stochastic discount factors. We extend their fundamental contribution by considering Minimum Discrepancy (MD) projections where misspecification is measured by...

Hansen and Jagannathan (1997) compare misspecified asset pricing models based on least-square projections on a family of admissible stochastic discount factors. We extend their fundamental contribution by considering Minimum Discrepancy (MD) projections where misspecification is measured by...

Based on a family of discrepancy functions, we derive nonparametric stochastic discount factor (SDFs) bounds that naturally generalize variance (Hansen and Jagannathan, 1991), entropy (Backus, Chernov and Martin, 2011), and higher-moment (Snow, 1991) bounds. These bounds are especially useful to...