Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization

International Journal of Approximate Reasoning

Volumn 55, Issue 3, 2014, Pages 812-833

  Singh, Pritpal ^a,b   Borah, Bhogeswar ^b  

^a THAPAR UNIVERSITY   (India)

^b TEZPUR UNIVERSITY   (India)

Author keywords

Defuzzification; Particle swarm optimization; Stock index forecasting; Type 1 fuzzy time series; Type 2 fuzzy time series

Indexed keywords

EID: 84894493014     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2013.09.014     Document Type: Article

References (61)

1. Q. Song, and B.S. Chissom Forecasting enrollments with fuzzy time series - part I Fuzzy Sets Syst. 54 1993 1 9
2. Q. Song, and B.S. Chissom Fuzzy time series and its models Fuzzy Sets Syst. 54 1993 1 9
3. Q. Song, and B.S. Chissom Forecasting enrollments with fuzzy time series - part II Fuzzy Sets Syst. 62 1994 1 8
4. S.M. Chen Forecasting enrollments based on fuzzy time series Fuzzy Sets Syst. 81 1996 311 319
5. C. Kai, F.F. Ping, and C.W. Gang A novel forecasting model of fuzzy time series based on k-means clustering Second International Workshop on Education Technology and Computer Science China 2010 223 225
6. H.-T. Liu, and M.-L. Wei An improved fuzzy forecasting method for seasonal time series Expert Syst. Appl. 37 2010 6310 6318
7. P. Singh, and B. Borah An efficient method for forecasting using fuzzy time series Machine Intelligence Tezpur University, Assam (India) 2011 Narosa India 67 75
8. S.-M. Chen, and K. Tanuwijaya Multivariate fuzzy forecasting based on fuzzy time series and automatic clustering techniques Expert Syst. Appl. 38 2011 10594 10605
9. J.R. Hwang, S.M. Chen, and C.H. Lee Handling forecasting problems using fuzzy time series Fuzzy Sets Syst. 100 1998 217 228
10. M. Sah, and K. Degtiarev Forecasting enrollment model based on first-order fuzzy time series Proceedings of World Academy of Sciences Engineering and Technology vol. 1 2005 132 135
11. C.H. Cheng, J.R. Chang, and C. Yeh Entropy-based and trapezoid fuzzification-based fuzzy time series approaches for forecasting IT project cost Technol. Forecast. Soc. Change 73 2006 524 542
12. C.H. Cheng, T.L. Chen, and C.H. Chiang Trend-weighted fuzzy time-series model for TAIEX forecasting I. King, J. Wang, L.-W. Chan, D. Wang, Neural Information Processing vol. 4234 2006 Springer-Verlag 469 477
13. J.-W. Wang, and J.-W. Liu Weighted fuzzy time series forecasting model Proceedings of the Second International Conference on Intelligent Information and Database Systems: Part I 2010 Springer-Verlag Hue, Vietnam 408 415
14. C.H. Aladag, M.A. Basaran, E. Egrioglu, U. Yolcu, and V.R. Uslu Forecasting in high order fuzzy times series by using neural networks to define fuzzy relations Expert Syst. Appl. 36 2009 4228 4231
15. C.H. Aladag, U. Yolcu, and E. Egrioglu A high order fuzzy time series forecasting model based on adaptive expectation and artificial neural networks Math. Comput. Simul. 81 2010 875 882
16. H.S. Lee, and M.T. Chou Fuzzy forecasting based on fuzzy time series Int. J. Comput. Math. 81 2004 781 789
17. W. Qiu, X. Liu, and H. Li A generalized method for forecasting based on fuzzy time series Expert Syst. Appl. 38 2011 10446 10453
18. W.-K. Wong, E. Bai, and A.W. Chu Adaptive time-variant models for fuzzy-time-series forecasting IEEE Trans. Syst. Man Cybern., Part B, Cybern. 40 2010 1531 1542
19. K.-H. Huarng, T.H.-K. Yu, and Y.W. Hsu A multivariate heuristic model for fuzzy time-series forecasting IEEE Trans. Syst. Man Cybern., Part B, Cybern. 37 2007 836 846
20. E.J. Bai, W.K. Wong, W.C. Chu, M. Xia, and F. Pan Heuristic time-invariant model for fuzzy time series forecasting Expert Syst. Appl. 38 2011 2701 2707
21. P. Singh, and B. Borah An effective neural network and fuzzy time series-based hybridized model to handle forecasting problems of two factors Knowl. Inf. Syst. 2013 1 22
22. P. Singh, and B. Borah High-order fuzzy-neuro expert system for time series forecasting Knowl.-Based Syst. 46 2013 12 21
23. J.-R. Chang, L.-Y. Wei, and C.-H. Cheng A hybrid ANFIS model based on AR and volatility for TAIEX forecasting Appl. Soft Comput. 11 2011 1388 1395
24. C.-H. Cheng, L.-Y. Wei, J.-W. Liu, and T.-L. Chen OWA-based ANFIS model for TAIEX forecasting Econ. Model. 30 2013 442 448
25. L.-Y. Wei A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting Appl. Soft Comput. 13 2013 911 920
26. J.-I. Park, D.-J. Lee, C.-K. Song, and M.-G. Chun TAIFEX and KOSPI 200 forecasting based on two-factors high-order fuzzy time series and particle swarm optimization Expert Syst. Appl. 37 2010 959 967
27. L.-Y. Hsu, S.-J. Horng, T.-W. Kao, Y.-H. Chen, R.-S. Run, R.-J. Chen, J.-L. Lai, and I.-H. Kuo Temperature prediction and TAIFEX forecasting based on fuzzy relationships and MTPSO techniques Expert Syst. Appl. 37 2010 2756 2770
28. I.-H. Kuo, S.-J. Horng, Y.-H. Chen, R.-S. Run, T.-W. Kao, R.-J. Chen, J.-L. Lai, and T.-L. Lin Forecasting TAIFEX based on fuzzy time series and particle swarm optimization Expert Syst. Appl. 37 2010 1494 1502
29. C.H. Aladag Using multiplicative neuron model to establish fuzzy logic relationships Expert Syst. Appl. 40 2013 850 853
30. K. Huarng, and H. Yu A type 2 fuzzy time series model for stock index forecasting Physica A 353 2005 445 462
31. W. Pedrycz, and M. Song Granular fuzzy models: a study in knowledge management in fuzzy modeling Int. J. Approx. Reason. 53 2012 1061 1079
32. S.F. Molaeezadeh, and M.H. Moradi A 2uFunction representation for non-uniform type-2 fuzzy sets: Theory and design Int. J. Approx. Reason. 54 2013 273 289
33. T. Kumbasar, I. Eksin, M. Guzelkaya, and E. Yesil Exact inversion of decomposable interval type-2 fuzzy logic systems Int. J. Approx. Reason. 54 2013 253 272
34. N.N. Karnik, and J.M. Mendel Applications of type-2 fuzzy logic systems to forecasting of time-series Inf. Sci. 120 1999 89 111
35. A. Mencattini, M. Salmeri, S. Bertazzoni, R. Lojacono, E. Pasero, and W. Moniaci Short term local meteorological forecasting using type-2 fuzzy systems Neural Nets Lecture Notes in Computer Science vol. 3931 2006 95 104
36. M. Almaraashi, and R. John Tuning fuzzy systems by simulated annealing to predict time series with added noise Proceedings of UKCI Essex, UK 2006 1 5
37. M. Almaraashi, and R. John Tuning of type-2 fuzzy systems by simulated annealing to predict time series Proceedings of the International Conference of Computational Intelligence and Intelligent Systems London 2011
38. K. Huarng Heuristic models of fuzzy time series for forecasting Fuzzy Sets Syst. 123 2001 369 386
39. K. Huarng Effective lengths of intervals to improve forecasting in fuzzy time series Fuzzy Sets Syst. 123 2001 387 394
40. I.-H. Kuo, S.-J. Horng, T.-W. Kao, T.-L. Lin, C.-L. Lee, and Y. Pan An improved method for forecasting enrollments based on fuzzy time series and particle swarm optimization Expert Syst. Appl. 36 2009 6108 6117
41. Y.-L. Huang, S.-J. Horng, M. He, P. Fan, T.-W. Kao, M.K. Khan, J.-L. Lai, and I.-H. Kuo A hybrid forecasting model for enrollments based on aggregated fuzzy time series and particle swarm optimization Expert Syst. Appl. 38 2011 8014 8023
42. M. Sheikhan, and N. Mohammadi Time series prediction using PSO-optimized neural network and hybrid feature selection algorithm for IEEE load data Neural Comput. Appl. 23 3-4 2012 1 10
43. L.A. Zadeh Fuzzy sets Inf. Control 8 1965 338 353
44. S. Greenfield, and F. Chiclana Accuracy and complexity evaluation of defuzzification strategies for the discretised interval type-2 fuzzy set Int. J. Approx. Reason. 54 2013 1013 1033
45. A. Mencattini, M. Salmeri, S. Bertazzoni, R. Lojacono, E. Pasero, and W. Moniaci Local meteorological forecasting by type-2 fuzzy systems time series prediction IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Giardini Naxos, Italy 2005 20 22
46. L.A. Zadeh The concept of a linguistic variable and its application to approximate reasoning - I Inf. Sci. 8 1975 199 249
47. T.-Y. Chen A signed-distance-based approach to importance assessment and multi-criteria group decision analysis based on interval type-2 fuzzy set Knowl. Inf. Syst. 2012 1 39
48. T. Ross Fuzzy Logic with Engineering Applications 2007 John Wiley and Sons Singapore
49. R. Eberhart, and J. Kennedy A new optimizer using particle swarm theory Proceedings of the Sixth International Symposium on Micro Machine and Human Science Nagoya 1995 39 43
50. R. Eberhart, and Y. Shi Particle swarm optimization: Developments, applications and resources Proceedings of the IEEE International Conference on Evolutionary Computation Brisbane, Australia 2001 591 600
51. T.-L. Lin, S.-J. Horng, T.-W. Kao, Y.-H. Chen, R.-S. Run, R.-J. Chen, J.-L. Lai, and I.-H. Kuo An efficient job-shop scheduling algorithm based on particle swarm optimization Expert Syst. Appl. 37 2010 2629 2636
52. S.-Y. Lin, S.-J. Horng, T.-W. Kao, D.-K. Huang, C.-S. Fahn, J.-L. Lai, R.-J. Chen, and I.-H. Kuo An efficient bi-objective personnel assignment algorithm based on a hybrid particle swarm optimization model Expert Syst. Appl. 37 2010 7825 7830
53. M. Martins, S. Fuchs, L. Pando, R. Luders, and M. Delgado PSO with path relinking for resource allocation using simulation optimization Comput. Ind. Eng. 65 2 2013
54. J. Kennedy, and R. Eberhart Particle swarm optimization IEEE International Conference on Neural Networks, vol. 4 Perth, WA 1995 1942 1948
55. I.C. Trelea The particle swarm optimization algorithm: convergence analysis and parameter selection Inf. Process. Lett. 85 2003 317 325
56. S.-M. Chen, and N.-Y. Chung Forecasting enrollments using high-order fuzzy time series and genetic algorithms Int. J. Intell. Syst. 21 2006 485 501
57. H. Theil Applied Economic Forecasting 1966 Rand McNally New York
58. H.-K. Yu Weighted fuzzy time series models for TAIEX forecasting Physica A 349 2005 609 624
59. S.-M. Chen Forecasting enrollments based on high-order fuzzy time series Cybern. Syst. 33 2002 1 16
60. A. Samvedi, and V. Jain A grey approach for forecasting in a supply chain during intermittent disruptions Eng. Appl. Artif. Intell. 26 3 2013
61. P. Singh, and B. Borah Indian summer monsoon rainfall prediction using artificial neural network Stoch. Environ. Res. Risk Assess. 27 7 2013 1 15