Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/13988
Autoria: | Bentes, S. R. Menezes, R. Mendes, D. A. |
Data: | 2008 |
Título próprio: | Long memory and volatility clustering: is the empirical evidence consistent across stock markets? |
Volume: | 387 |
Número: | 15 |
Paginação: | 3826-3830 |
ISSN: | 0378-4371 |
DOI (Digital Object Identifier): | 10.1016/j.physa.2008.01.046 |
Palavras-chave: | Long memory Volatility clustering ARCH type models Nonlinear dynamics Entropy |
Resumo: | Long memory and volatility clustering are two stylized facts frequently related to financial markets. Traditionally, these phenomena have been studied based on conditionally heteroscedastic models like ARCH, GARCH, IGARCH and FIGARCH, inter alia. One advantage of these models is their ability to capture nonlinear dynamics. Another interesting manner to study the volatility phenomenon is by using measures based on the concept of entropy. In this paper we investigate the long memory and volatility clustering for the SP 500, NASDAQ 100 and Stoxx 50 indexes in order to compare the US and European Markets. Additionally, we compare the results from conditionally heteroscedastic models with those from the entropy measures. In the latter, we examine Shannon entropy, Renyi entropy and Tsallis entropy. The results corroborate the previous evidence of nonlinear dynamics in the time series considered. |
Arbitragem científica: | yes |
Acesso: | Acesso Aberto |
Aparece nas coleções: | BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Long memory and volatility clustering.pdf | 96,17 kB | Adobe PDF | Ver/Abrir |
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