1. Support Vector Machine Regression for Volatile Stock Market Prediction Haiqin Yang, Laiwan Chan, and Irwin King Department of Computer Science and Engineering The Chinese University of Hong Kong August 12, 2002 IDEAL ’ 02

2. Outline  Support Vector Regression  Problem  Approaches (margin change)  Experiment & Results  Future works and Conclusions

3. Support Vector Regression  Developed by Vapnik (1995)  Model: Given Data  to estimate function:  by minimizing  –Insensitive loss function

4. Related Applications  Predicting time series with support vector machine (K.R.Muller etc. 1997)  Nonlinear prediction of chaotic time series using support vector machines(S.Mukherjee etc. 1997)  Support vector machine for regression and applications to financial forecasting (T.B.Trafalis etc. 2000)

5. Problem  –Insensitive loss function  the margin is symmetrical and fixed, insensitive and non-adaptive to the input data insensitive and non-adaptive to the input data

6.  Large margin  Small margin

7. Approaches (margin change)  Asymmetrical margin  Non-fixed margin

8.  general type of –Insensitive loss function  Lagrange multipliers are obtained from s.t.  Estimating function

9. Experiments  Model  Hang Seng Index.  Total data (104days) 15/01/2001 – 19/06/2001 15/01/2001 – 19/06/2001  Initial training data (84 days) 15/01/2001 – 22/05/2001 15/01/2001 – 22/05/2001  Procedure One-step ahead prediction One-step ahead prediction

10. Parameter Setting and Error Measurement  Algorithm is modified from LibSVM.  C = 6000  Kernel function (Radial Basis Function)  total error upside risk upside risk downside risk downside risk

11. Result  Fixed margin  Upside Risk

12. Result  Fixed margin  Downside Risk

13. Result  Fixed margin  Total Error

14. Result  Adaptive margin  Total Error

15. Conclusions  Proposed two approaches to set the margin :  Fixed and asymmetrical margin  Non-fixed and symmetrical margin  Compared these two approaches with original method with fixed and symmetrical margin

16. Future Works  Considering the case: non-fixed and asymmetrical margin  Adding some theoretical proofs about the observations

17. Q & A