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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 …
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We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … over the alternative volatility models in terms of mean absolute forecast errors and that (iii) forecast combinations …
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Based on a classical financial market model different model variants known from the literature are discussed and analyzed, each focussing on modeling financial markets as a nonlinear dynamic system by introducing the formation of (heterogeneous) beliefs about future asset prices into the model...
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