We employ a two-step estimation method to separate the upside and downside idiosyncratic volatility and examine its relation with future stock returns. We find that idiosyncratic volatility is negatively related to stock returns when the market is up and when it is down. The upside idiosyncratic...

This research note shows that the implied Black-Scholes volatility calculated using the bisection algorithm can have significant biases, which are more severe for in-themoney (ITM) options than for out-of-the-money (OTM) options. The biases are shown to have important implications as they could...

In this paper, we consider alternative approaches to the estimation of Itˆo diffusion processes from discretely sampled observations. Based on Monte Carlo simulation, we investigate the finite sample properties of various estimators and in particular compare the performance of the nonparametric...

Despite an extensive literature based on upper echelons theory and imprinting theory explores how top managers’ previous experience influence corporate behaviors, little is known about the impact of managers’ early policy-induced adversity experience on corporate social responsibility. This...

In this paper, we consider the estimation of Markov models where the transition density is unknown. The approach we propose is based on the empirical characteristic function estimation procedure with an approximate optimal weight function. The approximate optimal weight function is obtained...

Ang, Hodrick, Xing, and Zhang (2006a) show that stocks with high idiosyncratic return volatility tend to have low future returns. This paper further documents that idiosyncratic volatility is inversely related to future earning shocks, and more importantly, that the return-predictive power of...

This paper evaluates the performance of volatility forecasting based on stochastic volatility (SV) models. We show that the choice of squared asset-return residuals as a proxy for ex-post volatility directly leads to extremely low explanatory power in the common regression analysis of volatility...

In this paper, we propose a nonparametric estimator of the short rate diffusion process using observations of a panel of yields. The proposed estimator can greatly reduce the bias of the nonparametric estimator proposed in Stanton (1997) that uses a single time series of short rate observations....