Modelling and trading the London, New York and Frankfurt stock exchanges with a new gene expression programming trader tool
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DOI: 10.1002/isaf.1401
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- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Manahov, Viktor & Hudson, Robert & Hoque, Hafiz, 2015. "Return predictability and the ‘wisdom of crowds’: Genetic Programming trading algorithms, the Marginal Trader Hypothesis and the Hayek Hypothesis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 85-98.
- Shapiro, Arnold F., 2000. "A Hitchhiker's guide to the techniques of adaptive nonlinear models," Insurance: Mathematics and Economics, Elsevier, vol. 26(2-3), pages 119-132, May.
- Smith, Vernon L, 1982. "Markets as Economizers of Information: Experimental Examination of the "Hayek Hypothesis"," Economic Inquiry, Western Economic Association International, vol. 20(2), pages 165-179, April.
- Georgios Vasilakis & Konstantinos Theofilatos & Efstratios Georgopoulos & Andreas Karathanasopoulos & Spiros Likothanassis, 2013. "A Genetic Programming Approach for EUR/USD Exchange Rate Forecasting and Trading," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 415-431, December.
- Andreas Karatahansopoulos & Georgios Sermpinis & Jason Laws & Christian Dunis, 2014. "Modelling and Trading the Greek Stock Market with Gene Expression and Genetic Programing Algorithms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 596-610, December.
- Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
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