Betting against correlation: Testing theories of the low-risk effect

Abstract

We test whether the low-risk effect is driven by leverage constraints and, thus, risk should be measured using beta versus behavioral effects and, thus, risk should be measured by idiosyncratic risk. Beta depends on volatility and correlation, with only volatility related to idiosyncratic risk. We introduce a new betting against correlation (BAC) factor that is particularly suited to differentiate between leverage constraints and behavioral explanations. BAC produces strong performance in the US and internationally, supporting leverage constraint theories. Similarly, we construct the new factor SMAX to isolate lottery demand, which also produces positive returns. Consistent with both leverage and lottery theories contributing to the low-risk effect, we find that BAC is related to margin debt while idiosyncratic risk factors are related to sentiment.