volatility. This paper adopts a Bayesian approach to estimate stock price volatility. We find evidence that overall Bayesian … volatility estimates more closely approximate the implied volatility of stocks derived from traded call and put options prices … compared to historical volatility estimates sourced from IVolatility.com (“IVolatility”). Our evidence suggests use of the …

This paper proposes the sample path generation method for the stochastic volatility version of the CGMY process. We …

difficulties for the use of Fourier inversion methodologies in volatility surface calibration. Continuous time Markov chain …

In this paper, we modify Duan’s (1995) local risk-neutral valuation relationship (mLRNVR) for the GARCH option … more persistent in the risk-neutral measure than in the physical one, so that one is able to capture the variance risk … one-month variance swap rate, i.e., the CBOE Volatility Index (VIX) accurately. Our research suggests that one should use …

This study introduces a novel index based on expectations concordance for explaining stock-price volatility when novel … market volatility. Lower expectations concordance produces a stabilizing effect wherein the offsetting views reduce market … volatility. The empirical findings hold for ex post and ex ante measures of volatility and for OLS and GARCH estimates. …

implied volatility surface (up to 100%) and on two risk measures: value at risk and expected shortfall where an increase of up … functions in closed-form, which help with pricing and risk measure calculations. In a numerical example, we demonstrate the …

that information uncertainty is the channel through which innovation affects idiosyncratic risk. The results are robust for … rents; however, there is limited evidence regarding the impact of innovation on risk. We shed new light on how firms …' involvement in innovation activities impacts their volatility, particularly their idiosyncratic volatility. In this paper, we …

This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four … returns and expected risk. However, by using quantile regressions, we find that the risk-return relation moves from negative … to positive as the returns’ quantile increases. A positive risk-return relation is valid only in the upper quantiles. The …

This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of … an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are … studied separately. We start from the historical trend in the magnitude of risk and then turn to the relation between …