examines how well exchange rate volatility explains movements in stock market returns. The model-based predictions are …

Nonparametric methods for estimating the implied volatility surface or the implied volatility smile are very popular …. The first step requires to extract implied volatility data from observed option prices, in the second step the actual … and less tractable. In this study, we propose a one-step estimator for the implied volatility surface based on a least …

volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as … the Black-Scholes and Hull-White formulas which includes stochastic volatility. We find that long memory as well as …

on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new … directions. First, the realized variance is a much better estimate of the latent volatility than the sum of the weighted daily … squared returns. As such it is better suited for comparing the out-of-sample performances of competing volatility models …

optimizer. The mathematical motivation for such hybrid networks is presented, using the Kolmogorov theory of metric entropy. As … options written on the S&P 500 stock index. While option pricing theory typically requires a highly complex statistical model …

particularly interested in volatility modelling and forecasting given their importance for FOREX dealers. Compared with previous …

Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components … forecasts which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo …

forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo … linear compared to optimal forecasts is small. Extending the number of volatility components beyond what is feasible with MLE …