This study compares the efficacy of Black–Scholes implied volatility (BSIV) with model-free implied volatility (MFIV …) in providing volatility forecasts for 13 North American, European, and Asian stock market indexes: S&P 500 (United States … Kingdom). In-sample volatility forecasts show that both BSIV and MFIV significantly improve the fit of a GJR-GARCH(1,1) model …

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the … volatility as the implied volatility inferred from some artificial 'dynamically purified' price process that in theory allows to … order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived …

This paper evaluates the application of two well-known asymmetric stochastic volatility (ASV) models to option price … forecasting and dynamic delta hedging. They are specified in discrete time in contrast to the classical stochastic volatility (SV … volatility asymmetry on option pricing. The objectives of this paper are to estimate ASV option pricing models using a Bayesian …

Volatility long memory is a stylized fact that has been documented for a long time. Existing literature have two ways … to model volatility long memory: component volatility models and fractionally integrated volatility models. This paper … GARCH(1, 1) model by generating 37% less option pricing errors. With stronger volatility persistence, it also dominates a …

) lays the groundwork for the assessment of a firm's credit risk by its default probability. Doubtlessly, the volatility of … approach with conditional volatility models, we empirically examine in this article that the specification of conditional … volatility affects the probability of default and therefor the credit rating. More precisely, we show on German stock market data …

prices caused by stochastic volatility. -- option pricing ; autoregression ; heteroskedasticity ; GARCH ; leverage effect …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and …-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the …

price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the … jump component is persistent when forecasting the oil futures market volatility. Specifically, we propose a strategy that … according to their recent past forecasting performance. The volatility data are based on the intraday prices of West Texas …

virtually any stochastic volatility model model can be approximated arbitrarily well by a carefully chosen continuous time … illustrates these contributions of the paper, estimating a stochastic volatility jump diffusion model …