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- W2387263549 abstract "Considering factors of anticipation and volatility,to measure the dynamic character of higher moments risk and investigate impacts of the risk on multi-financial markets or assets,a model of multivariate conditional higher order moments,which can solve the problem of 'dimension disaster',was proposed with the determination of the formulas between moments and co-moments.Time-varying parameters of higher order moments were estimated using Dynamic Conditional Correlation,Autoregressive conditional density and intelligence optimization algorithm on distribution.The analysis on models shows that model of multivariate conditional higher order moments is better fitted with the feature of higher order moments of return series.Comparing our model with others,the model perform well in solving the problem of 'dimension disaster',which has implication that our model can catch the risk character of Chinese multi-markets and improve estimation in multivariate conditional higher order moments." @default.
- W2387263549 created "2016-06-24" @default.
- W2387263549 creator A5004534297 @default.
- W2387263549 date "2010-01-01" @default.
- W2387263549 modified "2023-09-26" @default.
- W2387263549 title "Modeling multivariate conditional variance skewness kurtosis" @default.
- W2387263549 hasPublicationYear "2010" @default.
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