Positive momentum:
Indices
θ27,Kt = ³
rsi5,Kt >80´
(58) θ28,Kt = ³
rsi5,Kt <20´
(59) θ29,Kt = ¡f iKt > f iKt−1¢
(60) θ30,Kt = ¡f iKt > f iKt−1¢ AN D ¡f iKt−1< f iKt−2¢
(61) θ31,Kt = ¡pviKt > pviKt−1¢
(62) θ32,Kt = ¡pviKt > pviKt−1¢ AN D ¡pviKt−16pviKt−2¢
(63)
References
Achelis, S. B.: 1995, Technical Analysis From A To Z, second printing edn, McGraw-Hill.
Allen, F. and Karjalainen, R.: 1999, Using genetic algorithms to find technical trading rules, Journal of Financial Economics 51, 245–79.
Altenberg, L.: 1994, Emergent phenomena in genetic programming, in A. Sebald and D. Fogel (eds), Proc. of the 3rd Annual Conference on Evolutionary Programming, World Scientific, pp. 233–241.
Angeline, P. J.: 1994, Genetic programming and emergent intelligence, in K. K. Jr. (ed.), Advances in Genetic Programming, MIT Press, pp. 75 – 98.
Banzhaf, W.: 1994, Genotype-phenotype mapping and neutral variation - a case study in genetic programming, in Y. Davidor, H. P. Schwefel and R.Maenner (eds), Parallel Prob-lem Solving from Nature - PPSN III, Vol. 866 of Lecture Notes in Computer Science, Springer-Verlag, pp. 322 – 332.
Banzhaf, W. and Langdon, W. B.: 2002, Some considerations on the reason for bloat, tbd . Banzhaf, W., Nordin, P., Keller, R. and Francone, F.: 1998, Genetic Programming - An
Introduction, Morgan Kaufmann.
Barberis, N. and Thaler, R.: 2003, A survey of behavioral finance, Elsevier Science B.V.
Black, F.: 1986, Noise, Journal of Finance 41, 529 – 543.
Bleuler, S., Brack, M., Thiele, L. and Zitzler, E.: 2001, Multiobjective genetic programming:
Reducing bloat using SPEA2, Proceedings of the 2001 Congress on Evolutionary Compu-tation CEC2001, IEEE Press, Seoul, Korea, pp. 536–543.
Brock, W., Lakonishok, J. and LeBaron, B.: 1992, Simple technical trading rules and the stochastic properties of stock returns, Journal of Finance 47, 1731 – 1764.
Bucher, M.: 2005, Evolutionary co-existence of rational and noise traders in a market with endogenous supply and demand, NCCR Fin Risk Working Paper .
Chekhlov, A., Uryasev, S. and Zabarankin, M.: 2005, Drawdown measure in portfolio opti-mization, International Journal of Theoretical and Applied Finance 8(1), 13 – 58.
Chen, S.-H.: 2002, Genetic Algorithms and Genetic Programming in Computational Finance, Kluwer Academics Publishers, Boston / Dordrecht / London.
Dempster, M. and Jones, C.: 2001, A real-time adaptive trading system using genetic pro-gramming, Quantitative Finance 1(4), 397 – 413.
Dempster, M. and Leemans, V.: 2004, An automated fx trading system using adaptive re-inforcement learning, Research papers in management studies, University of Cambridge pp. 1 – 19.
Diebold, F. X. and Mariano, R. S.: 1995, Comparing predictive accuracy, Journal of Business and Economic Statistics 13, 253 – 265.
Elder, A.: 1993, Trading for a living: psychology, trading tactics, money management, John Wiley and Sons.
Fama, E.: 1965, The behavior of stock market prices, The Journal of Business of the University of Chicago 38(1), 1–17.
Fama, E. and Blume, M.: 1966, Filter rules and stock-market trading, Journal of Business 39, 226 –241.
Freeman, J. J.: 1998, A linear representation for gp using contex free grammars, in J. R.
Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D. B. Fogel, M. H.Garzon, D. E.
Goldberg, H. Iba and R. L. Riolo (eds), Genetic Programming 1998: Proceedings of the 3rd Annual Conference, MIT Press, pp. 72 – 77.
Holland, J.: 1975, Adaptation in Natural and Artificial Systems, University of Michigan Press,
Kaufman, P. J.: 1987, The new commodity trading systems and methods, John Wiley and Sons, New York.
Keller, R. and Banzhaf, W.: 1996, Gp using mutation, reproduction and genotype-phenotype mapping from linear binary genomes into linear lalr phenotypes, in J. R. Koza, D. E.
Goldberg, D. B. Fogel and R. L. Riolo (eds), Genetic Programming 1996: Proceedings of the 1st Annual Conference, MIT Press, pp. 116 – 122.
Kogan, L., Ross, S., Wang, J., and Westerfield, M. M.: forthcoming, The price impact and survival of irrational traders, Journal of Finance .
Koza, J.: 1992, Genetic Programming: On the Programming of Computers by the Means of Natural Selection, MIT Press.
Levich, R. and Thomas, L.: 1993, The significance of trading rule profits in the foreign exchange market: A bootstrap approach, Journal of International Money and Finance 12, 451 – 474.
Lucas, R. E. J.: 1978, Asset prices in an exchange economy, Econometrica 46, 1429 – 1445.
Luke, S.: 2000, Issues in Scaling Genetic Programming: Breeding Strategies, Tree Generation and Bloat, PhD thesis, University of Maryland, College Park, MD, USA.
Luke, S. and Panait, L.: 2002, Lexicographic parsimony pressure, in C.-P. E. M. K. R. R. D.
D. P. R. B. K. H. V. R. G. W. J. B. L. P. M. S. A. M. J. B. E. J. N. In Langdon, W.B.
(ed.), Proceedings of GECCO – 2002, Morgan Kaufmann, San Francisco, CA, pp. 829 – 836.
Muth, J.: 1961, Rational expectations and the theory of price movements, Econometrica 29, 315 – 335.
Naur, P.: 1963, Revised report on the algorithmic language algol 60, Commun. ACM 6(1), 1–
17.
Neely, C., Weller, P. and Dittmar, R.: 1997, Is technical analysis in the foreign exchange market profitable? a genetic programming approach, Financial Quantitative Analysis 32, 405 – 426.
Neftci, S.: 1991, Naive trading rules in financial markets and wiener–kolmogorov prediction theory: A study of technical analysis, Journal of Business 64.
O’Neill, M. and Ryan, C.: 1999, Genetic code degeneracy: implications for grammatical evo-lution and beyond, ECAL’99: Proc. of the 5th European Conference on Artificial Life, Lausanne, Switzerland, pp. 149 – 153.
O’Neill, M. and Ryan, C.: 2001, Grammatical evolution, IEEE Transactions on Evolutionary Computation, Vol. 5, IEEE Press, pp. 349 – 358.
Osler, C. L. and Chang, P. K.: 1995, Head and shoulders: Not just a flaky pattern, Federal Reserve Bank of New York Staff Report 4, 1 –65.
Oussaidene, M., Chopard, B., Pictet, O. V. and Tomassini, M.: 1997, Parallel genetic program-ming and its application to trading model induction, Parallel Computing 23(8), 1183 – 1198.
Politis, D. and Romano, J.: 1994, The stationary bootstrap, Journal of the American Statistical Association 89, 1303 – 1313.
Ryan, C., Collins, J. and O’Neill, M.: 1998, Grammatical evolution: Evolving programs for an arbitrary language, EuroGP’98: Proceedings of the first European Workshop on Genetic Programming, Vol. 1391 of Lecture Notes in Computer Science, Springer Verlag, pp. 83–95.
Shleifer, A.: 2000, Inefficient Markets: An Introduction to Behavioral Finance, Oxford Uni-versity Press, Oxford, England.
Soule, T.: 1998, Code Growth in Genetic Programming, PhD thesis, University of Idaho, Moscow, ID, USA.
Soule, T. and Foster, J. A.: 1999, Effects of code growth and parsimony pressure on populations in genetic programming, Evoluationary Computation 4(6), 293 – 309.
Soule, T., Foster, J. A. and Dickinson, J.: 1996, Code growth in genetic programming, in J. R.
Koza, D. E. Goldberg, D. B. Fogel and R. L. Riolo (eds), Genetic Programming 1996:
Proceedings of the 1st Annual Conference, MIT Press, pp. 215 – 223.
Stanley, K. O. and Miikkulainen, R.: 2002, Efficient evolution of neural network topologies, Proceedings of the 2002 Congress on Evolutionary Computation (CEC ’02), IEEE Press.
Sullivan, R., Timmermann, A. and White, H.: 1999, Data snooping, technical trading rule performance and the bootstrap, Journal of Finance 54, 1647 – 1692.
Sweeney, R. J.: 1988, Some new filter rule tests: Methods and results, Journal of Financial and Quantitative Analysis 23, 285 – 300.
Taylor, S.: 1994, Trading futures using a channel rule: A study of the predictive power of technical analysis with currency examples, Journal of Futures Markets 14, 215 – 235.
West, K. D.: 1996, Asymptotic inference about predictive ability, Econometrica 64, 1067 – 1084.
Whigham, P.: 1995, Grammatically-based genetic programming, Proceedings of the Workshop on GP: From Theory to Real-World Applications, Morgan Kaufmann, pp. 33 – 41.
White, H.: 2000, A reality check for data snooping, Econometrica 68, 1097 – 1126.
Yu, T. and Bentley, P.: 1998, Methods to evolve legal phenotypes, in A. E. Eiben, T. Schoe-nauer and T. Baeck (eds), Parallel Problem Solving from Nature - PPSN V, Vol. 1498 of Lecture Notes in Computer Science, Springer-Verlag, pp. 280 – 291.
Zhang, B.-T. and Muehlenbein, H.: 1995, Balancing accuracy and parsimony in genetic pro-gramming, Evoluationary Computation 3(1), 17 – 38.
and the Gymnasium in Sarnen, he studied from 1994 to 1998 Economics at the „Ecole des Hautes Etudes Commerciales (HEC) “ of the University Lausanne, and at the University
„Carlos III“ in Madrid. Subsequently, he worked for Holcim and as a consultant for McKinsey
& Co. During the doctoral studies, he worked from 2001 to 2004 as a Financial Engineer for the Zurich Cantonal Bank.
Currently, he is employed as a Portfolio Manager in the systematic trading unit of the hedge fund Horizon21 Active Alpha.