PL EN


Preferences help
enabled [disable] Abstract
Number of results
2015 | 127 | 3A | A-129-A-135
Article title

Granger Causality and Transfer Entropy for Financial Returns

Content
Title variants
Languages of publication
EN
Abstracts
EN
Granger causality in its linear form has been shown by Barnett, Barrett and Seth [Phys. Rev. Lett. 103, 238701 (2009)] to be equivalent to transfer entropy in case of Gaussian distribution. Generalizations by Hlaváčková-Schindler [Appl. Math. Sci. 5, 3637 (2011)] are applied to distributions typical for biomedical applications. The financial returns, which are of great importance in financial econometrics, typically do not have Gaussian distribution. Generalizations leading to the concept of nonlinear Granger causality (e.g. causality in variance, causality in risk), known and applied in econometric literature, seem to be less known outside this field. In the paper an overview of some of the definitions and applications is given. In particular, we indicate some recent econometric results concerning application of the tests in linear multivariate framework. We emphasize importance of other variants of Granger causality, and need of development of methods reflecting features of financial variables.
Keywords
Year
Volume
127
Issue
3A
Pages
A-129-A-135
Physical description
Dates
published
2015-03
References
  • [1] Th. Schreiber, Phys. Rev. Lett. 85, 461 (2000), doi: 10.1103/PhysRevLett.85.461
  • [2] K. Hlávačková-Schindler, M. Paluš, M. Vejmelka, J. Bhattacharya, Phys. Rep. 441, 1 (2007), doi: 10.1016/j.physrep.2006.12.004
  • [3] L. Barnett, A. Barrett, A. Seth, Phys. Rev. Lett. 103 238701 (2009), doi: 10.1103/PhysRevLett.103.238701
  • [4] K. Hlaváčková-Schindler, Appl. Math. Sci. 5, 3637 (2011), doi: 10.1.1.407.6358
  • [5] L. Barnett, T. Bossomaier, Phys. Rev. Lett. 109, 138105 (2012), doi: 10.1103/PhysRevLett.109.138105
  • [6] R.F. Engle, Econometrics 50, 987 (1982), doi: 10.2307/1912773
  • [7] T. Bollerslev, J. Econometrics 31, 307 (1986), doi: 10.1.1.161.7380
  • [8] C. Alexander, Market Risk Analysis. Volume II. Practical Financial Econometrics, John Wiley, Chichester 2008
  • [9] B. Mandelbrot, J. Bus. 36, 394 (1963), doi: 10.1086/294632
  • [10] W. Feller, An Introduction to Probability Theory and Its Applications, Vol. II, John Wiley, New York 1957
  • [11] S.T. Rachev, Y.S. Kim, M.L. Bianchi, Frank J. Fabozzi Series: Financial Models with Lévy Processes and Volatility Clustering, John Wiley, Hoboken, NJ 2011
  • [12] M. Osińska, Ekonometryczna analiza zależności przyczynowych, Wydawnictwo Naukowe Uniwersytetu Mikołaja Kopernika, Toruń, 2008
  • [13] M.T. Subbotin, Matematicheskii Sbornik 31, 296 (1923)
  • [14] P. Theodossiou, SSRN 11, 1 (2000), doi: 10.2139/ssrn.219679
  • [15] R.S. Tsay, Analysis of Financial Time Series, 3rd ed., John Wiley, Hoboken 2007
  • [16] E.M. Syczewska, Metody Ilościowe w Badaniach Ekonomicznych XV/4, 169 (2014)
  • [17] C.W.J. Granger, Econometrica 37, 424 (1969), doi: 10.2307/1912791
  • [18] K. Hlaváčková-Schindler, Causality in Time Series: Its Detection and Quantification by Means of Information Theory, in: Information Theory and Statistical Learning, Ed. F. Emmert-Streib, M. Dehmer, Springer-Verlag, New York 2009, p. 183
  • [19] L. Barnett, A.K. Seth, J. Neurosci. Meth. 223, 50 (2014), doi: 10.1016/j.jneumeth.2013.10.018
  • [20] C.W.J. Granger, J. Econ. Dyn. Control 2 329 (1980), doi: 10.1016/0165-1889(80)90069-X
  • [21] C.W.J. Granger, J. Econometrics 112, 69 (2003), doi: 10.1016/S0304-4076(02)00148-3
  • [22] M. Osińska, J. Stawicki, Testing for causality across spectral frequency bands, in: Some aspects of the dynamic econometric modelling, Ed. Z. Zieliński, Wydawnictwo Uniwersytetu Mikołaja Kopernika, Toruń 1993, p. 135
  • [23] A.G. Malliaris, J.L. Urrutia, J. Financ. Quant. Anal. 27, 353 (1992), doi: 10.2307/2331324
  • [24] J.F. Geweke, J. Am. Stat. Assoc. 77, 304 (1982), doi: 10.1080/01621459.1982.10477803
  • [25] C.A. Sims, Am. Econ. Rev. 62, 540 (1972)
  • [26] G. Chamberlain, Econometrica 50, 569 (1982), doi: 10.2307/1912601
  • [27] G.E.P. Box, G.M. Jenkins, Time Series Analysis. Forecasting and control, Holden-Day, San Francisco 1976
  • [28] C.W.J. Granger, R.F. Engle, Econometrica 55, 251 (1987), doi: 10.2307/1913236
  • [29] S. Johansen, Likelihood-based inference in cointegrated vector autoregressive models, Oxford University Press, Oxford 1995
  • [30] T. Bossomaier, L. Barnett, M. Harré, Complex Adaptive Systems Modeling 1, 9 (2013), doi: 10.1186/2194-3206-1-9
  • [31] H.Y. Toda, T. Yamamoto, J. Econometrics 66, 225 (1995), doi: 10.1016/0304-4076(94)01616-8
  • [32] D. Bauer, A. Maynard, J. Econometrics 169, 293 (2012), doi: 10.1016/j.jeconom.2012.01.023
  • [33] P. Jizba, H. Kleinert, M. Shefaat, Physica A 391, 2971 (2012), doi: 10.1016/j.physa.2011.12.064
  • [34] J. Bruzda, Procesy nieliniowe i zależności długookresowe w ekonomii. Analiza kointegracji nieliniowej, Wydawnictwo Naukowe Uniwersytetu Mikołaja Kopernika, Toruń 2007
  • [35] C.W.J. Granger, E. Maasoumi, J. Racine, J. Time Series Analysis 25, 649 (2004), doi: 10.1111/j.1467-9892.1994.tb00200.x
  • [36] C.W.J. Granger, T. Teräsvirta, Modelling Nonlinear Economic Relationships, Oxford University Press, Oxford 1993
  • [37] C.W.J. Granger, J.-L. Lin, J. Time Series Analysis 15, 371 (1994), doi: 10.1111/j.1467-9892.1994.tb00200.x
  • [38] J. Bruzda, AUNC 34, 183 (2004)
  • [39] W. Orzeszko, Przegląd Statystyczny 59, 369 (2012)
  • [40] C. Hiemstra, J.D. Jones, J. Financ. 49, 1639 (1994), doi: 10.1111/j.1540-6261.1994.tb04776.x
  • [41] R. Arellano-Valle, J.E. Contreras-Reyes, M.G. Genton, Scand. J. Stat. 40, 42 (2012), doi: 10.2307/23357252
  • [42] A.K. Seth, J. Neurosci. Meth. 186, 262 (2010), doi: 10.1016/j.jneumeth.2009.11.020
Document Type
Publication order reference
YADDA identifier
bwmeta1.element.bwnjournal-article-appv127n3a23kz
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.