A Forex trading expert system based on a new approach to the rule-base evidential reasoning

Expert Systems with Applications

Volumn 51, Issue , 2016, Pages 1-13

  Dymova, Ludmila ^a   Sevastjanov, Pavel ^a   Kaczmarek, Krzysztof ^a  

^a CZESTOCHOWA UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Dempster Shafer theory; Expert system; Forex; Fuzzy logic; Rule base evidential reasoning; Technical analysis

Indexed keywords

COMMERCE; COMPUTER CIRCUITS; ECONOMICS; EXPERT SYSTEMS; FINANCIAL MARKETS; FORMAL LOGIC; FUZZY LOGIC; MEMBERSHIP FUNCTIONS; PROBABILISTIC LOGICS; RECONFIGURABLE HARDWARE; TIME SERIES ANALYSIS;

DEMPSTER-SHAFER THEORY; DEMPSTER-SHAFER THEORY OF EVIDENCE; EVIDENTIAL REASONING; FOREX; FUZZY LOGIC RULES; MECHANICAL TRADING; TECHNICAL ANALYSIS; TIME SERIES PREDICTION;

ELECTRONIC TRADING;

EID: 84954214792     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2015.12.028     Document Type: Article

References (52)

1. Amiri M., Zandieh M., Vahdani B., Soltani R., and Roshanaei V. An integrated eigenvectorDEATOPSIS methodology for portfolio risk evaluation in the FOREX spot market Expert Systems with Applications 37 2010 509 516
2. Baba N., and Kozaki M. An intelligent forecasting system of stock price using neural networks Proceedings of IJCNN'92 1992 317 377
3. Bagheri A., Peyhani H.M., and Akbari M. Financial forecasting using ANFIS networks with quantum-behaved particle swarm optimization Expert Systems with Applications 41 2014 6235 6250
4. Bahrepour M., M.-R. Akbarzadeh-T., Yaghoobi M., and M.-B. Naghibi-S. An adaptive ordered fuzzy time series with application to FOREX Expert Systems with Applications 38 2011 475 485
5. Binaghi E., Gallo I., and Madella P. A neural model for fuzzy Dempster-Shafer classifiers International Journal of Approximate Reasoning 25 2000 89 121
6. Binaghi E., and Madella P. Fuzzy Dempster-Shafer reasoning for rule-based classifiers International Journal of Intelligent Systems 14 1999 559 583
7. Delmotte F., Dubois L., Desodt A., and Borne P. Using trust in uncertainty theories Information and Systems Engineering 1 1995 303 314
8. Dempster A.P. Upper and lower probabilities induced by a multi-valued mapping Annals of Mathematical Statistics 38 1967 325 339
9. Dempster A.P. A generalization of Bayesian inference (with discussion) Journal of the Royal Statistical Society 30 2 1968 208 247 Series B.
10. Dourra H., and Siy P. Investment using technical analysis and fuzzy logic Fuzzy Sets and Systems 127 2002 221 240
11. Dubois D., and Prade H. A Set-Theoretic View on Belief Functions: Logical Operations and Approximations by Fuzzy Sets International Journal of General Systems 12 1986 193 226
12. Dubois D., and Prade H. Representation and combination of uncertainty with belief functions and possibility measures Computational Intelligence 4 1988 244 264
13. Dubois D., and Prade H. Representation and combination of uncertainty with belief functions and possibility measures Computational Intelligence 4 1998 244 264
14. Dymova L., Sevastianov P., and Bartosiewicz P. A new approach to the rule-base evidential reasoning: Stock trading expert system application Expert Systems with Applications 37 2010 5564 5576
15. Dymova L., Sevastianov P., and Kaczmarek K. A stock trading expert system based on the rule-base evidential reasoning using Level 2 Quotes Expert Systems with Applications 39 2012 7150 7157
16. Sentz, and Ferson S. Combination of evidence in Dempster-Shafer theory Technical report, 2002 SANDIA National Laboratories
17. Florea M., Dezert J., Valin P., Smarandache F., and Jousselme A. Adaptative combination rule and proportional conflict redistribution rule for information fusion Cognitive systems with interactive sensors, Paris 2006 cs/0604042v1
18. Gottschlich J., and Hinz O. A decision support system for stock investment recommendations using collective wisdom Decision Support Systems 59 2014 52 62
19. Haefke C., and Helmenstein C. Predicting stock market averages to enhance profitable trading strategies Proceedings of the third international conference on neural networks in the capital markets, London 2000 378 389
20. Hu Y., Feng B., Zhang X., Ngai E.W.T., and Liu M. Stock trading rule discovery with an evolutionary trend following model Expert Systems with Applications 42 2015 212 222
21. Inagaki T. Interdependence between Safety-Control Policy and Multiple-Sensor Schemes Via Dempster-Shafer Theory IEEE Transactions on Reliability 40 1991 182 188
22. Ishizuka M., Fu K.S., and Yao J.T.P. Inference procedure and uncertainty for the problem reduction method Information Sciences 28 1982 179 206
23. Kao L.-J., Chiu C.-C., Lu C.-J., and Chang C.-H. A hybrid approach by integrating wavelet-based feature extraction with MARS and SVR for stock index forecasting Decision Support Systems 54 2013 1228 1244
24. Kendall S.M., and Ord K. Time series 3rd 1990 Oxford University Press New York
25. Kim K.J., and Han I. Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index Expert Systems with Applications 19 2000 125 132
26. Kuo R.J., Chen C.H., and Hwang Y.C. An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network Fuzzy Sets and Systems 118 2001 21 45
27. Liu W. Analizing the degree of conflict among belief functions Artificial Intelligence 170 2006 909 924
28. Mahfoud S., and Mani G. Financial forecasting using genetic algorithms Applications of Artificial Intelligence 10 1996 543 566
29. Mamdani E., and Assilian S. An experiment in linguistic synthesis with a fuzzy logic controller International Journal of Man-Machine Studies 1 1975 1 13
30. Martin A., Osswald C., Dezert J., and Smarandache F. General Combination Rules for Qualitative and Quantitative Beliefs Journal of Advances in Information Fusion 3 2008 67 89
31. Mehta K., and Bhattacharyya S. Adequacy of training data for evolutionary mining of trading rules Decision Support Systems 37 2004 461 474
32. Mendes L., Godinho P., and Dias J. A Forex trading system based on a genetic algorithm Journal of Heuristics 18 2012 627 656
33. Murphy C.K. Combining belief functions when evidence conflicts Decision Support Systems 29 2000 1 9
34. Pang S., Song L., and Kasabov N. Correlation-aided support vector regression for forex time series Neural Computing and Applications 20 2011 1193 1203
35. Patel J., Shah S., Thakkar P., and Kotecha K. Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques Expert Systems with Applications 42 2015 259 268
36. Pawlak Z. Rough sets International Journal of Information and Computer Science 11 1982 145 172
37. Santiprabhob P., Nguyen H.T., Pedrycz W., and Kreinovich V. Logic-motivated choice of fuzzy logic operators Proceedings of the 2015 IEEE international conference on fuzzy systems (FUZZ-IEEE 2015) 2001 646 649
38. Sevastianov P., and Dymova L. Synthesis of fuzzy logic and Dempster-Shafer theory for the simulation of the decision-making process in stock trading systems Mathematics and Computers in Simulation 80 2009 506 521
39. Sewastianow P., and Rozenberg P. Optimal investment using technical analysis and fuzzy logic Proceedings of the international conference on fuzzy sets and soft computing in economics and finance 2004 St. Petersburg 415 422
40. Shafer G. A mathematical theory of evidence 1976 Princeton University Press Princeton
41. Shen L., and Loh H.T. Applying rough sets to market timing decisions Decision Support Systems 37 2004 583 597
42. Shmilovici A., Kahiri Y., and Ben-Gal I. Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm Computational Economics 33 2009 31 154
43. Smarandache F. Unification of Fusion Theories (UFT) 2005 NATO Advanced Study Institute Albena, Bulgaria 16 27
44. Smets P. The alpha-junctions: combination operators applicable to belief functions Lecture Notes in Computer Science vol. 1244 1997 Springer 131 153
45. Turksen I.B., Kreinovich V., and Yager R.R. A new class of fuzzy implications (axioms of fuzzy implication revisited) Fuzzy Sets and Systems 100 1998 267 272
46. Wang Y.F. Mining stock price using fuzzy rough set system Expert Systems with Applications 24 2003 13 23
47. Yager R.R. Generalized probabilities of fuzzy events from belief structures Information Sciences 28 1982 45 62
48. Yager R.R., and Filev D.P. Including probabilistic uncertainty in fuzzy logic controller modeling using Dempster-Shafer theory IEEE Transactions on Systems, Man Cybernetics 25 1995 1221 1230
49. Yang J.B., Liu J., Wang J., Sii H.S., and Wang H. Belief rule-base inference methodology using the evidential reasoning approach - RIMER IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans 36 2 2006 266 285
50. Yang J.B., Liu J., Xu D.L., Wang J., and Wang H. Optimization models for training belief-rule-based systems IEEE Transactions on Systems, Man and Cybernetics, Part A-Systems and Humans 37 4 2007 569 585
51. Yen J. Generalizing the Dempster-Shafer theory to fuzzy sets Systems, Man and Cybernetics, IEEE Transactions on 20 1990 559 570
52. Zadeh L. A simple view of the Dempster-Shafer theory of evidence and its application for the rule of combination AI Magazine 7 1986 85 90