Giglio, Ricardo and Da Silva, Sergio (2009): Ranking the stocks listed on Bovespa according to their relative efficiency. Published in: Applied Mathematical Sciences , Vol. 43, No. 3 (2009): pp. 2133-2142.
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Abstract
A methodology based on the algorithmic complexity theory has been applied to assess the relative efficiency of the stocks listed on Bovespa. We provide eight alternative listings of the top ten stocks according to their efficiency rates.
Item Type: | MPRA Paper |
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Original Title: | Ranking the stocks listed on Bovespa according to their relative efficiency |
Language: | English |
Keywords: | Algorithmic complexity theory; Econophysics; Financial efficiency |
Subjects: | G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading C - Mathematical and Quantitative Methods > C0 - General |
Item ID: | 22720 |
Depositing User: | Sergio Da Silva |
Date Deposited: | 19 May 2010 03:29 |
Last Modified: | 04 Oct 2019 16:23 |
References: | [1] J. Y. Campbell, A. W. Lo, A. C. MacKinley, The Econometrics of Financial Markets, Princeton University Press, Princeton, 1997. [2] R. Giglio, R. Matsushita, S. Da Silva, The relative efficiency of stockmarkets, Economics Bulletin, 7(2008a), 1−12. [3] R. Giglio, R. Matsushita, A. Figueiredo, I. Gleria, S. Da Silva, Algorithmic complexity theory and the relative efficiency of financial markets, Europhysics Letters, 84(2008b), 48005. [4] F. Kaspar, H. G. Schuster, Easily calculable measure for the complexity of spatiotemporal patterns, Physical Review A, 36(1987), 842–848. [5] A. Lempel, J. Ziv, On the complexity of finite sequences, IEEE Transactions on Information Theory, 22(1976), 75–81. [6] R. N. Mantegna, H. E. Stanley, An Introduction to Econophysics: Correlations and Complexity in Finance, Cambridge University Press, Cambridge, 2000. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/22720 |