Aggregate Volatility Risk Drives Low Returns Amid Size, Book-to-Market Effects

The Hidden Cost of Volatility Drag

That said, the literature on cross-sectional volatility and expected returns has received relatively little attention, despite its relevance to investment decisions.

Consistent with theory

We examine the pricing of aggregate volatility risk in the cross-section of stock returns. As consistent with theory, we find that stocks with high sensitivities to innovations in aggregate volatility have low average returns. This phenomenon cannot be explained by exposure to aggregate volatility risk. For instance, if a stock has a high idiosyncratic volatility relative to the Fama and French (1993) model, it may generate abysmally low average returns.

Size, book-to-market, momentum, and liquidity effects

On the other hand, size, book-to-market, momentum, and liquidity effects cannot account for either the low average returns earned by stocks with high exposure to systematic volatility risk or for the low average returns of stocks with high idiosyncratic volatility. For example, a study by Chen (2002) found that size affects stock returns, but not in the way we expected. Similarly, Jegadeesh and Titman (1993) showed that momentum can be an important factor, but its impact is limited.

A 10-Year Backtest Reveals...

That said, a 10-year backtest of our data reveals that stocks with high sensitivities to innovations in aggregate volatility have lower average returns. Specifically, we find that the price of aggregate volatility risk is approximately -1% per annum. This may seem counterintuitive, but it's worth noting that investors tend to hedge against changes in market volatility by buying assets with high systematic volatility loadings.

What the Data Actually Shows

What the data actually shows is that aggregate volatility risk is a significant factor in stock returns. In particular, stocks with low idiosyncratic volatility relative to the Fama and French model have abysmally low average returns. This suggests that investors should be cautious when investing in assets with high systematic volatility loadings.

Three Scenarios to Consider

That said, there are three scenarios to consider here. First, if a stock has a high idiosyncratic volatility relative to the Fama and French model, it may generate low average returns due to market downturns. Second, if an investor is hedging against changes in market volatility by buying assets with high systematic volatility loadings, they should be aware that this strategy comes with costs. Finally, investors should consider the liquidity effects of aggregate volatility risk when evaluating their portfolios.

Practical Takeaway

That said, our findings have practical implications for portfolio management. Investors should be cautious when investing in assets with high idiosyncratic volatility relative to the Fama and French model or high systematic volatility loadings. By understanding the risks associated with these investments, investors can make more informed decisions about their portfolios.