Exchange rates determination based on genetic algorithms using mendel's principles: Investigation and estimation under uncertainty

Information Fusion

Volumn 14, Issue 3, 2013, Pages 327-333

  Chen, Yi ^a,b   Zhang, Guangfeng ^b,c  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF GLASGOW   (United Kingdom)

^c BRUNEL UNIVERSITY   (United Kingdom)

Author keywords

Estimation; Exchange rates; Genetic algorithm; High frequency; Mendel's principle; Regression; Uncertainty

Indexed keywords

ESTIMATION; FINANCE; FREQUENCY ESTIMATION; MATLAB;

EXCHANGE RATES; HIGH FREQUENCY HF; MENDEL'S PRINCIPLE; REGRESSION; UNCERTAINTY;

GENETIC ALGORITHMS;

EID: 84880447443     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.inffus.2011.12.003     Document Type: Article

References (39)

1. M. Obstfeld, K. Rogoff, The six major puzzles in international macroeconomics: is there a common cause?, NBER Working Papers 7777, 2000.
2. K. Rogoff, The purchasing power parity puzzle, Journal of Economic Literature 34 (1996) 647-668. (Pubitemid 126420563)
3. R. Lyons, The Microstructure Approach to Exchange Rates, MIT Press, London, England, 2001.
4. W.P. Killeen, R.K. Lyons, M.J. Moore, Fixed versus flexible: lessons from ems order flow, Journal of International Money and Finance 25 (2006) 551-579. (Pubitemid 43758392)
5. R. Payne, Informed trade in spot foreign exchange markets: An empirical investigation, Journal of International Economics 61 (2003) 307-329. (Pubitemid 37250132)
6. T.H. Hann, E. Steurer, Much ado about nothing? exchange rate forecasting: neural networks vs. linear models using monthly and weekly data, Neurocomputing 10 (1996) 323-339. (Pubitemid 26170371)
7. M. Qi, Y. Wu, Nonlinear prediction of exchange rates with monetary fundamentals, Journal of Empirical Finance 10 (2003) 623-640. (Pubitemid 36910251)
8. R.N. Yadav, P.K. Kalra, J. John, Time series prediction with single multiplicative neuron model, Applied Soft Computing 7 (2007) 1157-1163. (Pubitemid 46810390)
9. S. Rimcharoen, D. Sutivong, P. Chongstitvatana, Prediction of the stock exchange of thailand using adaptive evolution strategies, in: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence, IEEE Computer Society, Washington, DC, USA, 2005.
10. C. Worasucheep, P. Chongstitvatana, A multi-strategy differential evolution algorithm for financial, Prediction with Single Multiplicative Neuron, ICONIP 2009, Part II, LNCS, vol. 5864, 2009, pp. 122-130.
11. J. Nenortaite, R. Simutis, Stocks' Trading System Based on the Particle Swarm Optimization Algorithm, Workshop on Computational Methods in Finance and Insurance, Lecture Notes in Computer Science, vol. 3039/2004, Springer, 2004.
12. L. Zhao, Y. Yang, Expert systems with applications: pso-based single multiplicative neuron model for time series prediction, Expert Systems with Applications 36 (2009) 2805-2812.
13. J.H. Holland, Adaptation in Natural and Artificial Systems, The University of Michigan Press, 1975.
14. G. Mendel, Experiments in Plant Hybridization, 1865. www.mendelweb.org/ Mendel.html.
15. D. O'Neil, Mendel's Genetics, 2009.
16. I.S. Song, H.W. Woo, M.J. Tahk, A genetic algorithm with a Mendel operator for global minimization, in: Proceedings of the 1999 Congress on Evolutionary Computation, Washington, DC, USA, vol. 2, 1999, pp. 1521-1526.
17. C.S. Park, H. Lee, H.C. Bang, M.J. Tahk, Modified mendel operation for multimodal function optimization, in: Proceedings of the 2001 Congress on Evolutionary Computation, Seoul, South Korea, vol. 2, 2001, pp. 1388-1392. (Pubitemid 32806301)
18. B. Anthony Kadrovach, S.R. Michaud, J.B. Zydallis, G.B. Lamont, B. Secrest, D. Strong, Extending the simple genetic algorithm into multi-objective problems via mendelian pressure, 2001 Genetic and Evolutionary Computation Conference, San Francisco, California, 7-11 July, vol. 1, 2001, pp. 181-188.
19. B.A. Kadrovach, J.B. Zydallis, G.B. Lamont, Use of mendelian pressure in a multi-objective genetic algorithm, in: Proceedings of the 2002 Congress on Evolutionary Computation, Piscataway, New Jersey, 12-17 May, vol. 1, 2002, pp. 962-967.
20. H. Ishibuchi, T. Yoshida, T. Murata, Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling, IEEE Transactions on Evolutionary Computation 7 (2003) 204-223.
21. Victoria Furió, Andrés Moya, Rafael Sanjuán, The cost of replication fidelity in an RNA virus, Proceedings of the National Academy of Sciences 102 (2005) 10233-10237.
22. E. Zitzler, Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications, Diss. ETH No. 13398, ETH Zurich, Switzerland, 1999.
23. The National Academy of Sciences (NAS), Teaching about Evolution and the Nature of Science, National Academy of Sciences Press, 2004.
24. R.L. Haupt, S.E. Haupt, Practical Genetic Algorithms, second ed., John Wiley & Sons, Inc., 2004.
25. C.M. Fonseca, P.J. Fleming, Genetic algorithm for multi-objective optimisation: formulation, discussion and generalization, in: S. Forrest (Ed.), Genetic Algorithm: Proceedings of the Fifth International Conference, vol. 1, Morgan Kaufmann, San Mateo, CA, 1993, pp. 141-153.
26. J.N. Horn, D.E.N. Goldberg, A niched pareto genetic algorithm for multiobjective optimisation, in: Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, 27-29 June, vol. 1, 1994, pp. 82-87.
27. N. Srinivas, K. Deb, Multiobjective optimisation using nondominated sorting in genetic algorithm, Evolutionary Computation 2 (1994) 221-248.
28. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGAII, IEEE Transactions on Evolutionary Computation 6 (2002) 182-197. (Pubitemid 34555372)
29. P. Tenti, Forecasting foreign exchange rates using recurrent neural networks, Applied Artificial Intelligence 10 (1996) 567-581. (Pubitemid 126683323)
30. D.N. Gujarati, Basic Econometrics, fourth ed., McGraw-Hill Companies, 2004.
31. S. Reitz, M.A. Schmidt, M.P. Taylor, End-user order flow and exchange rate dynamics, The European Journal of Finance 17 (2011) 153-168.
32. D. Rime, L. Sarno, E. Sojli, Exchange rate forecasting, order flow, and macroeconomic information, CEPR Discussion Paper No. DP7225, 2009. Available at SSRN:
33. T. Andersen, T. Bollerslev, F.X. Diebold, C. Vega, Microeffects of macroannouncements: real-time price discovery in foreign exchange, American Economic Review 93 (2003) 38-62. (Pubitemid 38799486)
34. P. Bacchetta, E. Wincoop, Can information heterogeneity explain the exchange rate determination puzzle?, American Economic Review 96 (2006) 552-576. (Pubitemid 44273970)
35. J. Marks, The construction of mendel's laws, Evolutionary Anthropology 17 (2008) 250-253.
36. D.C. Montgomery, G.C. Runger, Applied Statistics and Probability for Engineers, third ed., John Wiley & Sons, Inc., 2003.
37. M. Evans, R. Lyons, Order flow and exchange rate dynamics, Journal of Political Economy 110 (2002) 170-180. (Pubitemid 34186558)
38. M.P. Allen, Understanding Regression Analysis, Springer, 2007.
39. Y. Chen, Simple Genetic Algorithm Laboratory Toolbox for MATLAB, 2009. http://www.mathworks.co.uk/matlabcentral/fileexchange/5882.