Measuring Nonlinear Serial Dependencies Using the Mutual Information Coefficient
DOI:
https://doi.org/10.12775/DEM.2010.008Keywords
nonlinearity, mutual information coefficient, mutual information, serial dependenciesAbstract
Construction, estimation and application of the mutual information measure have been presented in this paper. The simulations have been carried out to verify its usefulness to detect nonlinear serial dependencies. Moreover, the mutual information measure has been applied to the indices and the sector sub-indices of the Warsaw Stock Exchange.
References
Barnett W. A., Gallant A. R., Hinich M. J., Jungeilges J. A., Kaplan D., Jensen M. J. (1998), A Single-blind Controlled Competition among Tests for Nonlinearity and Chaos, Journal of Econometrics, 82.1, 157–192.
Bruzda J. (2004), Miary zależności nieliniowej w identyfikacji nieliniowych procesów ekonomicznych (Measures of nonlinear relationship in identification of nonlinear economic processes), Acta Universitatis Nicolai Copernici, 34, 183–203.
Darbellay G.A, Wuertz D. (2000), The entropy as a tool for analysing statistical dependencies in financial time series, Physica A, 287, 429–439.
Dionisio A., Menezes R., Mendes D.A. (2003), Mutual Information: a Dependence Measure for Nonlinear Time Series, Working Paper, http://129.3.20.41/eps/em/papers/0311//0311003.pdf (10.02.2010).
Fonseca N., Crovella M., Salamatian K. (2008), Long Range Mutual Information, Proceedings of the First Workshop on Hot Topics in Measurement and Modeling of Computer Systems (Hotmetrics ’08), Annapolis.
Fraser A.M., Swinney H.L. (1986), Independent Coordinates for Strange Attractors from Mutual Information, Physical Review A, 33.2, 1134–1140.
Granger C. W. J., Terasvirta T. (1993), Modelling Nonlinear Economic Relationship, Oxford University Press, Oxford.
Granger C. W. J., Lin J-L. (1994), Using the Mutual Information Coefficient to Identify Lags in Nonlinear Models, Journal of Time Series Analysis, 15, 371–384.
Maasoumi E., Racine J. (2002), Entropy and Predictability of Stock Market Returns, Journal of Econometric”, 107, 291–312. DOI: http://dx.doi.org/10.1016/S0304-4076(01)00125-7
Orzeszko W. (2010), Detection of Nonlinear Autodependencies Using Hiemstra-Jones Test, Financial Markets. Principles of Modeling, Forecasting and Decision-Making, eds. Milo W., Szafrański G., Wdowiński P., 157–170.
Downloads
Published
How to Cite
Issue
Section
License
The journal provides an Open Access to its content based on the non-exclusive licence Creative Commons (CC BY-ND 4.0).
To enable the publisher to disseminate the author's work to the fullest extent, the author must agrees to the terms and conditions of the License Agreement with Nicolaus Copernicus University.
Stats
Number of views and downloads: 346
Number of citations: 0
