On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns
研究发现，用EGARCH模型估计当月特质波动率时，若包含当月收益会导致虚假的正相关关系，这种前瞻性偏差在股票收益偏斜和样本长度下问题显著，而用前期数据估计则关系消失。
Abstract A spurious positive relation between exponential generalized autoregressive conditional heteroskedasticity (EGARCH) estimates of expected month t idiosyncratic volatility and month t stock returns arises when the month t return is included in estimation of model parameters. We illustrate via simulations that this look-ahead bias is problematic for empirically observed degrees of stock return skewness and typical monthly return time series lengths. Moreover, the empirical idiosyncratic risk-return relation becomes negligible when expected month t idiosyncratic volatility is estimated using returns only up to month t − 1.