Recurrent self-organising maps and local support vector machine models for exchange rate prediction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3973 LNCS, Issue , 2006, Pages 504-511

  Ni, He ^a   Yin, Hujun ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

INTERNATIONAL TRADE; MATHEMATICAL MODELS; REGRESSION ANALYSIS; STATISTICAL METHODS; VECTOR QUANTIZATION;

GARCH METHOD; NON-STATIONARY FINANCIAL TIME SEQUENCE DATA; RECURRENT SELF-ORGANISING MAP(RSOM); SUPPORT VECTOR MACHINES;

SELF ORGANIZING MAPS;

EID: 33745903869     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11760191_74     Document Type: Conference Paper

References (17)

1. Hamilton, J.; Time Series Analysis, Princeton University Press (1994)
2. Engle, R.: Autoregressive Conditional Heteroskedasticity with Estimates of The Variance of United Kingdom Inflation. Econometrics 50 (1982) 987-1007
3. Bollerslev, T.; Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics 31 (1986) 307-327
4. Kim, T.Y., Oh, K.J., Kim, C., Do, J.D.: Artificial Neural Networks for Non-stationary Time Series. Neurocomputing 61 (2004) 439-447
5. Vesanto, J.: Using The SOM and Local Models in Time-Series Prediction. Helsinki University of Technology. (1997) B15
6. Cao, L.J.: Support Vector Machines Experts for Time Series Forecasting. Neurocomputing 51 (2002) 321-339
7. Koskela, T.: Time Series Prediction Using Recurrent SOM with Local Linear Models. Helsinki University of Technology (2001)
8. Martinetz, T.M., Berkovich, S.G., Schulten, K.J.; "Neural-Gas" Network for Vector Quantization and Its Application to Time Series Prediction. IEEE Transactions on Neural Networks 4 (1993) 558-569
9. Kohonen, T.: Self-Organizing Maps. Springer, Berlin (1995)
10. Vapnik, V.: The Nature of Statistical Learning Theory. Springer, New York (1995)
11. Walter, J., Ritter, H., Schulten, K.: Nonlinear Prediction with Self-Organizing Maps. Beckman-Institute and Department of Physics, UIUC, Urbana.
12. Freeman, R.T., Yin, H.: Adaptive Topological Tree Structure for Document Organisation and Visualisation. Neural Networks 17 (2004) 1255-1271
13. Chappell, G.J., Taylor, J.G.: The Temporal Kohonen Map. Neural Networks 4 (1993) 441-445
14. Koskela, T., Varsta, M., Heikkonen, J., Kaski, K.: Time series Prediciton Using Recurrent SOM with Local Linear Model. Report B15, Lab. of Computational Engineering, Helsinki University of Technology, Oct (1997)
15. Yin, H.: Self-Organising Map as A Natural Kernel Method. Proc. ICNN&B'05, Beijing, China, 13-15 Oct. (2005)
16. Kuhn, H.W., Tucker, A.W.: Nonlinear Programming. Proc. 2nd Berkeley Symposium on Mathematical Statistics and Probabilistics. 481C492, (1951) University of California Press, Berkeley
17. Hyvarinen, A., Oja, E.: Independent Component Analysis: Algorithms and Applications. Neural Networks 13(4-5) (2000) 411-430