Composite of adaptive support vector regression and nonlinear conditional heteroscedasticity tuned by quantum minimization for forecasts

Applied Intelligence

Volumn 27, Issue 3, 2007, Pages 277-289

  Chang, Bao Rong ^a   Tsai, Hsiu Fen ^b  

^a NATIONAL TAITUNG UNIVERSITY   (Taiwan)

^b SHU TE UNIVERSITY   (Taiwan)

Author keywords

Adaptive support vector regression; Nonlinear generalized autoregressive conditional heteroscedasticity; Quantum minimization; Volatility clustering

Indexed keywords

ADAPTIVE SYSTEMS; COMPUTATIONAL COMPLEXITY; GENETIC ALGORITHMS; MATHEMATICAL MODELS; SUPPORT VECTOR MACHINES; TIME SERIES ANALYSIS;

ADAPTIVE SUPPORT VECTOR REGRESSION (ASVR); NONLINEAR GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (NGARCH); QUANTUM MINIMIZATION; VOLATILITY CLUSTERING;

TECHNOLOGICAL FORECASTING;

EID: 34948883358     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-006-0036-9     Document Type: Article

References (29)

1. Box GEP, Jenkins GM, Reinsel GC (1994) Time series analysis: forecasting & control. Prentice-Hall, New Jersey
2. Deng JL (1982) Control problems of grey system. Syst Control Lett 1(5):288-294
3. Chang BR (2003) A study of non-periodic short-term random walk forecasting based on RBFNN, ARMA, or SVR-GM(1,1,tau) approach. In: Proceedings of the IJCNN, pp 254-259
4. Vapnik V (1995) The nature of statistical learning theory. Springer-Verlag, New York
5. Chang BR (2005) Compensation and regularization for improving the forecasting accuracy by adaptive support vector regression. Int J Fuzzy Syst 7(3):110-119
6. Bellerslve T (1986) Generalized autoregressive conditional heteroscedasticity. J Econ 31:307-327
7. Gourieroux C (1997) ARCH models and financial applications. Springer-Verlag, New York
8. Nielsen MA, Chuang IL (2000) Quantum computation and quantum information. Cambridge University Press, London, ISBN 0 521 63503 9
9. Anguita D, Ridella S, Rivieccio F, Zunino R (2003) Training support vector machines-a quantum-computing perspective. In: International joint conference on neural network IJCNN03, pp 1587-1592
10. Durr C, Hoyer P (1996) A quantum algorithm for finding the minimum, http://arxiv.org/abs/quant-ph/9607014
11. Fletcher R (1987) Practical methods of optimization, 2nd edn. Wiley and Sons, New York
12. Deutsch D, Jozsa R (1992) Rapid solution of problems by quantum computation. In: Proceedings of the Royal Society, London, A439, pp. 553-558
13. Grover LK (1996) A fast quantum mechanical algorithm for database search. In: Proceedings of the 28th annual ACM symposium theory of comp. ACM Press, pp 212-219
14. Boyer M, Brassard G, Hoyer P, Tapp A (1998) Tight bounds on quantum searching. Fortschritte Der Physik
15. Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines. Cambridge University Press, London
16. Kreyszig E (1999) Advanced engineering mathematics, 8th edn. Wiley, New York
17. Chang CC, Lin CJ (2003) LIBSVM: a library for support vector machines, http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm. pdf
18. Murphey YL, Chen ZH, Putrus M, Feldkamp L (2003) SVM learning from large training data set. In: Proceedings of the IEEE IJCNN, pp 860-2865
19. Hamilton JD (1994) Time series analysis. Princeton University Press, New Jersey
20. Hentschel L (1995) All in the family: Nesting symmetric and asymmetric GARCH models. J Finan Econ 39:71-104
21. Huang YP, Yu TM (1997) The hybrid grey-based models for temperature prediction. IEEE Trans. SMC-Part B: Cybernetics 27(2):284-297
22. Mori H, Kosemura N, Ishiguro K, Kondo T (2001) Short-term load forecasting with fuzzy regression tree in power systems. In: Proceedings of the IEEE international conference on SMC, pp 1948-1953
23. Chang BR (2006) Applying nonlinear generalized autoregressive conditional heteroscedasticity to compensate ANFIS outputs tuned by adaptive support vector regression. Fuzzy Sets Syst 157(13):1832-1850
24. Pshenichnyj BN, Wilson SS (1994) The linearization method for constrained optimization. Springer, New York
25. Ono I, Kobayashi S (1997) A real-coded genetic algorithm for function optimization using unimodal normal distribution crossover. In: Proceedings of the 7th international conference genetic Algorithms, pp 246-253
26. Diebold FX (1998) Elements of forecasting. South-Western, Cincinnati.
27. FIBV FOCUS MONTHLY STATISTICS (2005) International Stock Price Index
28. Ljung GM, Box GEP (1978) On a measure of lack of fit in time series models. Biometrika 65:67-72
29. Central Weather Bureau, Typhoon Moving Trace Inquire, Taipei, Taiwan, 2005