My research evolves around aggregate volatility risk and the effects of idiosyncratic volatility on expected returns. The central idea is presented in my job market paper. High idiosyncratic volatility means lower beta of growth options, because it lowers their sensitivity to the value of the underlying asset. Idiosyncratic volatility also creates the idiosyncratic volatility hedging channel. In recessions, idiosyncratic volatility is high, and it mutes the increase of the risk premium. The idiosyncratic volatility hedging channel is the strongest for high volatility firms and growth firms. Its presence explains why the existing models cannot explain the effects of idiosyncratic volatility on returns.

The idiosyncratic volatility channel works through changes in aggregate volatility and associated changes in idiosyncratic volatility. Therefore, it is natural to summarize the business cycle sensitivity it predicts by looking at the return sensitivity to aggregate volatility changes. In my job market paper, I predict and find that high volatility firms and growth firms have less negative current return reaction to aggregate volatility increases. When bad news about future aggregate volatility arrives and all prices slide down, their expected returns go up the least. In other words, high volatility firms and growth firms have lower exposure to aggregate volatility risk.

The link between idiosyncratic volatility and expected returns I find in my thesis opens the gate to rethinking numerous asset-pricing puzzles. First, it shows that high idiosyncratic uncertainty about the future of the firm should mean lower, not higher expected returns. I successfully used this fact to explain the underperformance of new issues, and plan to use it to explain the diversification discount. I also believe that the low or non-existent return premium to firms in low-quality or volatile information environment (high and volatile turnover, bad accounting practices, earnings management, low disclosure) can be explained by the failure of the respective studies to control for the idiosyncratic volatility discount.

Second, I believe that it is time to rethink the results of many papers that treat idiosyncratic volatility as the limits to arbitrage proxy. My papers offer a risk-based story of why idiosyncratic volatility impacts future returns. So, the fact that the strength of most anomalies is related to idiosyncratic volatility does not necessarily mean their irrational nature. Rather, it can mean that they are related to aggregate volatility risk and business cycle risk.

The model I use in my thesis to explain the idiosyncratic volatility discount can be modified to explain other anomalies. Any option-like characteristic of the firm can be used to generate the idiosyncratic volatility discount, to influence its magnitude, and to change the firm exposure to aggregate volatility risk. For example, the anomalous low return to highly levered firms can be explained by my model. It implies that idiosyncratic volatility can create hedges via leverage as well, and highly levered firms will be hedges against aggregate volatility risk.

Also, what matters in my model is the total idiosyncratic volatility during the life of the real option. Holding the duration of the life fixed, it creates the idiosyncratic volatility discount. Holding idiosyncratic volatility per time unit fixed, it creates the duration discount. The duration discount is likely to be related to the value effect, as my model would predict. Studying this relation can shed light on why growth firms have low cash flow beta and high discount rate beta, and why the former commands high risk premium, and the latter commands low risk premium.

1. Idiosyncratic Volatility, Growth Options, and the Cross-Section of Returns, Job Market Paper

   I develop a real options model showing that high idiosyncratic volatility lowers conditional betas of growth options and their exposure to aggregate volatility risk. I predict and find that the idiosyncratic volatility discount is much stronger for growth firms and is absent for value firms. I show empirically that the exposure to the aggregate volatility risk completely explains the idiosyncratic volatility discount and the stronger idiosyncratic volatility discount for growth firms. Aggregate volatility risk also partly explains the stronger value effect for high volatility firms. I also find that high volatility, growth, and especially high volatility growth firms have much lower betas in recessions.

2. Aggregate Volatility Risk: Explaining the Small Growth Anomaly and the New Issues Puzzle

   I show that the aggregate volatility risk factor (BVIX factor) explains the well-known underperformance of small growth firms. The BVIX factor also reduces the underperformance of IPOs and SEOs by 45\% and makes it statistically insignificant. The BVIX factor is unrelated to the investment factor proposed by Lyandres, Sun, and Zhang (2007) and has similar explanatory power. The BVIX factor is more helpful than the investment factor in explaining stronger new issues underperformance for small firms and growth firms. The investment factor is better at capturing the change in the underperformance in event time. The BVIX factor is also successful in explaining low returns to high cumulative issuance firms and the stronger cumulative issuance puzzle for growth firms.

1. The Idiosyncratic Volatility Discount and the Size Effect

   Small firms usually have high idiosyncratic volatility. The size effect says they should earn high returns. The idiosyncratic volatility says just the opposite. This is why the size effect seems weak. When I sort stocks on residual size, orthogonalized to idiosyncratic volatility, I find the size effect alive and well in all periods. Sorting on residual size also eliminates the small growth anomaly and the negative size effect for growth firms. Residual size sorts produce a better pricing factor I call RSMB. RSMB is less correlated with HML and BVIX. Replacing SMB with RSMB makes the HML betas of new issues large and negative instead of zero.

2. Idiosyncratic Volatility and Continuation Anomalies

   I hypothesize that high volatility losers are low-risk firms, because the option-like nature of leverage makes volatile losers a good hedge against aggregate volatility risk. I find that the relation between momentum and idiosyncratic volatility is indeed strong for highly levered firms and absent for low leverage firms. This result is primarily driven by the low returns earned by high volatility losers. I also find that business-cycle related variables are able to predict most of the momentum differential between high and low volatility portfolios.

3. Idiosyncratic Volatility, Growth Options, and Earnings Announcements

   I predict that the hedging ability of high volatility and growth firms against adverse aggregate volatility shocks is greater when idiosyncratic volatility is high. Idiosyncratic volatility is high at earnings announcements. I argue that the well-known underperformance of growth stocks around earnings announcements can be explained by the risk shift. I find a similar pattern for the idiosyncratic volatility discount, especially if it is measured for growth stocks. The underperformance of growth and high volatility firms around earnings announcements can be traced back to the decrease in their HML and BVIX betas.

4. The Idiosyncratic Volatility Discount and Conservative Accounting

   One of the attributes of high-quality accounting is conservatism. In the light of the recent evidence that low idiosyncratic risk firms earn high future returns, I hypothesize that conservative accounting firms also earn high future returns. I estimate the conservatism premium to be around 15 bp per month. The conservatism premium appears unrelated to the size effect, the accrual anomaly, and even the idiosyncratic volatility discount. I find that the conservatism premium is higher for growth stocks and can be partly explained by the exposure to aggregate volatility risk. I also find that the conservatism premium is higher for highly levered firms.