) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This …

(unit roots in levels together with fat tails in returns and volatility clustering). Our time series analysis of simulated …

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 …

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

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering … phenomenological volatility models analyzed in LeBaron [25], the usual statistical tests are not able to distinguish between true or …

Simulations of agent-based models have shown that the stylized facts (unit-root, fat tails and volatility clustering … phenomenological volatility models analyzed in LeBaron [25], the usual statistical tests are not able to distinguish between true or …