Abstract
The cointegration between individual stocks and the index is conditional on a number of variables to account for company-specific fundamentals and non-linear dynamics. This paper describes a methodology for selecting relative value stocks using the principle of non linear cointegration. The forecast of the cointegration residuals is being made using neural networks in order to capture any short-run dynamics in the estimation process. The trading rules that were applied indicate that consistent profits can be realised. However, the magnitude of the profits that most stocks have generated was relatively small. A closer look in the results justified that the performance was heavily penalised due to the effect of trading costs. The reason appears to be that too many buy/sell signals were suggested by the model which conceal the real performance of the cointegration model. The above may be attributed to the fact that market imperfections such as trading costs are not incorporated within the cointegration relationship and the forecasting model. We are introducing some preliminary ideas on the problem of incorporating market imperfections in the modeling process and the need for tests and measures (such as cyclicity tests) that may accomplish that.
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References
Burgess A.N. and Refenes A.P. (1995) “Modelling non-linear cointegration in international equity index futures” in Neural Networks in Financial Engineering A.P. Refenes et al.
Engle R.F and C.W.J Granger (1987) “Co-integration and error correction: representation, estimation and testing”, Econometrica, Vol. 55, pp.251–276.
Granger C.W.J. (1986) “Developments in the study of cointegrated economic variables”, Oxford Bulletin of Economics and Statistics, Vol. 48, pp. 213–228.
Holden K and J. Thompson (1992) “Cointegration: an introductory survey”, British Review of Economic Issues, Vol. 14, No.3
Refenes A.P. (1995) Neural Networks in the Capital Markets, Wiley
Refenes A.P., Abu-Mostafa Y., Moody J., Weigend A., Neural Networks in Financial Engineering Proc. Of the 3rd NNCM, World Scientific
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© 1998 Springer Science+Business Media Dordrecht
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Kollias, C., Metaxas, K. (1998). Selecting Relative-Value Stocks with Non Linear Cointegration. In: Refenes, AP.N., Burgess, A.N., Moody, J.E. (eds) Decision Technologies for Computational Finance. Advances in Computational Management Science, vol 2. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5625-1_14
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DOI: https://doi.org/10.1007/978-1-4615-5625-1_14
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-7923-8309-3
Online ISBN: 978-1-4615-5625-1
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