One of the reason that suggests to use COGARCH models to fit financial log-return data is due to the fact that they are able to capture the so called stylized facts observed in real data: uncorrelated log-returns but correlated absolute log-return, time varying volatility, conditional heteroscedasticity, cluster in volatility, heavy tailed and asymmetric unconditional distributions, leverage effects. The aims of this paper is to fit the COGARCH models to a real financial data set, estimate the parameters of the models via the prediction based estimating functions and to look at the performance of these estimates.
Cogarch models: A statistical application / Negri, I.; Bibbona, E.. - In: STATISTICA & APPLICAZIONI. - ISSN 1824-6672. - 15:2(2017), pp. 151-164.
Titolo: | Cogarch models: A statistical application |
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Data di pubblicazione: | 2017 |
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Digital Object Identifier (DOI): | http://dx.doi.org/10.26350/999999_000008 |
Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/11583/2831737