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期刊名称: Information Sciences: An International Journal
Volume:267(null)     2014
ISSN:0020-0255

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作者 : Rui Jorge Almeida ;   Nalan Ba?türk ;   Uzay Kaymak ;   Jo?o M.C. Sousa ;  
发表期刊 : Information Sciences: An International Journal
ISSN : 0020-0255
出版时间 : 2014
卷期 : 267(null)
起始页码 : 252
终止页码 : 266
总页数 : 15
英文摘要 : In this work we introduce a new flexible fuzzy GARCH model for conditional density estimation. The model combines two different types of uncertainty, namely fuzziness or linguistic vagueness, and probabilistic uncertainty. The probabilistic uncertainty is modeled through a GARCH model while the fuzziness or linguistic vagueness is presented in the antecedent and combination of the rule base system. The fuzzy GARCH model under study allows for a linguistic interpretation of the gradual changes in the output density, providing a simple understanding of the process. Such a system can capture different properties of data, such as fat tails, skewness and multimodality in one single model. This type of models can be useful in many fields such as macroeconomic analysis, quantitative finance and risk management. The relation to existing similar models is discussed, while the properties, interpretation and estimation of the proposed are provided. The model performance is illustrated in simulated time series data exhibiting complex behavior and a real data application of volatility forecasting for the S&P 500 daily returns series.
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