This paper introduces a model-independent measure of aggregate idiosyncratic risk based on the mean-variance portfolio theory and the concept of gain from portfolio diversification. With the new approach, there is no need to estimate the covariance terms or the industry-level or firm-level beta...

Using two large hedge fund databases, this paper empirically tests the presence and significance of a cross-sectional relation between hedge fund returns and value at risk (VaR). The univariate and bivariate portfolio-level analyses as well as the fund-level regression results indicate a...

We investigate the cross-sectional return predictability of delta-hedged equity options using machine learning and big data. Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample...

This paper shows that firm growth potential – representing a firm's yet-unexercised growth opportunities – is associated with option overpricing and low future delta-hedged option returns. We provide an explanation of this phenomenon based on the idea that retail investors exert buying...

We introduce a measure of regret for stock market investors and investigate its cross-sectional asset pricing implications. We propose a theoretical framework in which investors experience regret due to not achieving the highest possible return in the same industry with their stock investment,...

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...

Motivated by the nature of asset pricing models, we investigate the cross-sectional relation between the market's ex-ante view of a stock's risk and the stock's ex-ante expected return. We demonstrate that an ex-ante measure of expected returns based on analyst price targets is highly related to...

We derive a measure of aggregate systemic risk, designated CATFIN, that complements bank-specific systemic risk measures by forecasting macroeconomic downturns six months into the future using out-of-sample tests conducted with US, European and Asian bank data. Consistent with bank...