Common Idiosyncratic Quantile Factors and Asset Prices

TL;DR

This paper uses quantile factor analysis to identify common shocks affecting firm-specific return tails, revealing a significant downside premium that persists after controlling for standard risk factors and predicts market returns.

Contribution

It introduces a novel quantile factor analysis approach to uncover common idiosyncratic tail risks and demonstrates their pricing effects and predictive power for market returns.

Findings

High-beta stocks outperform low-beta stocks by 7-8% annually.

Downside tail factor is more pronounced with weak capital and low liquidity.

Downside factor predicts aggregate market excess returns.

Abstract

We investigate whether the tails of firm-level idiosyncratic return distributions are driven by common shocks. We use quantile factor analysis to extract such common idiosyncratic quantile factors with asymmetric pricing effects and we find a significant premium for innovations to the lower-tail factor: high-beta stocks outperform low-beta stocks by around 7-8% per year. This premium remains significant even when controlling for standard factors, idiosyncratic volatility and tail-risk measures. The downside factor strengthens when intermediary capital is weak and market liquidity is low, and it predicts aggregate market excess returns.