Identifying Stock Option Mispricing at a Large Cross Section
提出两步法从大量期权中识别隐含波动率错误定价，分离历史波动率与公司特征的影响，构建多空策略获得高信息比率，对交易成本稳健。
ABSTRACT This paper introduces an innovative two‐step approach for identifying implied volatility (IV) mispricing across a large cross‐section, moving beyond the traditional volatility forecasting framework. The two‐step process disentangles the contributions of historical volatility and other firm‐specific characteristics, isolating the residual as the IV mispricing. Different from traditional IV misvaluation proxies, which primarily focus on 1‐month at‐the‐money (ATM) options, our method demonstrates broader applicability. It accommodates options with wider maturities and extends to both ATM and out‐of‐the‐money (OTM) call and put options. Applying a long‐short delta‐hedged options trading strategy, using the IV mispricing, achieves a high information ratio (IR). When incorporating short‐ and long‐term historical volatility trends as conditions, while returns remain relatively unchanged, portfolio volatility is significantly reduced, further enhancing the IR to 4.093. This approach provides a robust predictive signal for option returns and remains resilient to transaction costs, consistently outperforming alternative signals, as validated through double‐sorting analysis.