Showing 1 - 7 of 7
is used for innovations. As the association between the underlying assets may vary over time, the dynamic copula approach …-GH model with time-varying copula differ substantially from the prices implied by the GARCH-Gaussian dynamic copula model …
Persistent link: https://www.econbiz.de/10010738494
Heteroskedastic (GARCH) process. As the association between the underlying assets may vary over time, the dynamic copula with time …-varying parameter offers a better alternative to any static model for dependence structure and even to the dynamic copula model … Shanghai and Shenzhen Stock Composite Indexes. Results show that the option prices obtained by the time-varying copula model …
Persistent link: https://www.econbiz.de/10010738655
In this paper we deal with the problem of non-stationarity encountered in a lot of data sets, mainly in financial and economics domains, coming from the presence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. Existence of non-stationarity involves spurious behaviors...
Persistent link: https://www.econbiz.de/10010750362
In this paper we deal with the problem of non-stationarity encountered in a lot of data sets coming from existence of multiple seasonnalities, jumps, volatility, distorsion, aggregation, etc. We study the problem caused by these non stationarities on the estimation of the sample autocorrelation...
Persistent link: https://www.econbiz.de/10010750670
Heteroskedastic (GARCH) process. As the association between the underlying assets may vary over time, the dynamic copula with time …-varying parameter offers a better alternative to any static model for dependence structure and even to the dynamic copula model … Shanghai and Shenzhen stock composite indexes. Results show that the option prices obtained by the time-varying copula model …
Persistent link: https://www.econbiz.de/10010750766
is used for innovations. As the association between the underlying assets may vary over time, the dynamic copula approach …-GH model with time-varying copula differ substantially from the prices implied by the GARCH-Gaussian dynamic copula model …
Persistent link: https://www.econbiz.de/10010750828
This chapter recalls the main tools useful to compute Value at Risk associated with a m-dimensional portfolio. Then, the limitations of the use of these tools is explained, as soon as non-stationarities are observed in time series. Indeed, specific behaviours observed by financial assets, like...
Persistent link: https://www.econbiz.de/10010603681