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- Financial_models_with_long-tailed_distributions_and_volatility_clustering abstract "Financial models with long-tailed distributions and volatility clustering have been introduced to overcome problems with the realism of classical financial models. These classical models of financial time series typically assume homoskedasticity and normality cannot explain stylized phenomena such as skewness, heavy tails, and volatility clustering of the empirical asset returns in finance. In 1963, Benoit Mandelbrot first used the stable (or -stable) distribution to model the empirical distributions which have the skewness and heavy-tail property. Since -stable distributions have infinite -th moments for all , the tempered stable processes have been proposed for overcoming this limitation of the stable distribution. On the other hand, GARCH models have been developed to explain the volatility clustering. In the GARCH model, the innovation (or residual) distributions are assumed to be a standard normal distribution, despite the fact that this assumption is often rejected empirically. For this reason, GARCH models with non-normal innovation distribution have been developed.Many financial models with stable and tempered stable distributions together with volatility clustering have been developed and applied to risk management, option pricing, and portfolio selection.".
- Financial_models_with_long-tailed_distributions_and_volatility_clustering wikiPageID "18443436".
- Financial_models_with_long-tailed_distributions_and_volatility_clustering wikiPageRevisionID "577422487".
- Financial_models_with_long-tailed_distributions_and_volatility_clustering hasPhotoCollection Financial_models_with_long-tailed_distributions_and_volatility_clustering.
- Financial_models_with_long-tailed_distributions_and_volatility_clustering subject Category:Actuarial_science.
- Financial_models_with_long-tailed_distributions_and_volatility_clustering subject Category:Mathematical_finance.
- Financial_models_with_long-tailed_distributions_and_volatility_clustering subject Category:Stochastic_models.
- Financial_models_with_long-tailed_distributions_and_volatility_clustering comment "Financial models with long-tailed distributions and volatility clustering have been introduced to overcome problems with the realism of classical financial models. These classical models of financial time series typically assume homoskedasticity and normality cannot explain stylized phenomena such as skewness, heavy tails, and volatility clustering of the empirical asset returns in finance.".
- Financial_models_with_long-tailed_distributions_and_volatility_clustering label "Financial models with long-tailed distributions and volatility clustering".
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- Financial_models_with_long-tailed_distributions_and_volatility_clustering sameAs Q5449732.
- Financial_models_with_long-tailed_distributions_and_volatility_clustering sameAs Q5449732.
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