, especially on the BS implied volatility. Implied binomial trees (IBT) models capture the variations of the implied volatility … known as volatility smile. They provide a discrete approximation to the continuous risk neutral process for the underlying … Barle and Cakici (BC). After the formation of IBT we can estimate the implied local volatility and the state price density …

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this … stochastic volatility models. The empirical analysis on stock returns on the US market shows that 1% and 5 % Value …

Market analysts and central banks often use the implied volatility of FX options as an indicator of expected exchange … deviate the value of implied volatility from the exchange rate variability expected by the market. These biasing factors are … one month. However, implied volatility provides a biased estimate, and does not encompass the information included in …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

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 …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

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 …