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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Bentes, S. & Menezes, R. (2016). An entropy approach to financial volatility: Evidence from the G7 countries. VBSF - 2016 Vietnam Symposium of Banking and Finance.
Exportar Referência (IEEE)
S. M. Bentes and R. M. Menezes,  "An entropy approach to financial volatility: Evidence from the G7 countries", in VBSF - 2016 Vietnam Symp. of Banking and Finance, Hanoi, 2016
Exportar BibTeX
@misc{bentes2016_1766520488908,
	author = "Bentes, S. and Menezes, R.",
	title = "An entropy approach to financial volatility: Evidence from the G7 countries",
	year = "2016",
	howpublished = "Outro",
	url = ""
}
Exportar RIS
TY  - CPAPER
TI  - An entropy approach to financial volatility: Evidence from the G7 countries
T2  - VBSF - 2016 Vietnam Symposium of Banking and Finance
AU  - Bentes, S.
AU  - Menezes, R.
PY  - 2016
CY  - Hanoi
AB  - A survey on the subject shows that the most commonly used measure of stock market volatility has been the standard deviation. However, since it can only account
for linear phenomena we purpose an alternative approach based on the concept of entropy, whose main advantage lies on the fact that it makes possible a more
comprehensive description of such volatility. In view of the fact that the Shannon entropy is only suitable for describing systems in a state of equilibrium, a generalization of it –Tsallis entropy – is additionally considered. This measure is suitable for describing anomalous systems, into which category financial markets appear to fall. More specifically, a comparison is made in this research between the results of the traditional approach based on the standard deviation and the ones provided by Shannon and Tsallis entropies. A sample is used consisting of the returns of the main stock market indexes of the G7 countries. The results show the limitations of the standard deviation-based approach in fully characterizing the oscillations of
volatility.
ER  -