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 …

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 …

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 …

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 …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular …

finance. The major attraction of these processes is their ability to generate various degrees of long memory in different … 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 …

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 …