In this work we compare the prediction performance of three optimized technical indicators with a Support Vector Machine Neural Network. For the indicator part we picked the common used indicators: Relative Strength Index, Moving AverageConvergence Divergence and Stochastic Oscillator. For the Support Vector Machine we used a radial-basis kernel function and regression mode. The techniques were applied on financial time series brought from the Swedish stock market. The comparison and the promising results should be of interest for both finance people using the techniques in practice, as well as software companies and similar considering to implement the techniques in their products.
Contents
1 Introduction
2 BACKGROUND
3 PROBLEM DEFINATION
4 Pre Processing
4.1 SPLIT CORRECTIONS
4.2 DETRENDING
4.3 DATA PARTITIONING
4.4 RESCALING
4.5 PRINCIPAL COMPONENT ANALYSIS
5 SUPPORT VECTOR MACHINES
5.1 INTRODUCTION
5.2 PREDICTION ACCOMPLISHMENT
6 TECHNICAL INDICATORS
6.1 RELATIVE STRENGTH INDEX
6.2 MOVING AVERAGES
6.3 STOCHASTIC OSCILLATOR
6.4 MOVING AVERAGE CONVERGENCE DIVERGENCE
6.5 OPTIMIZATION
7 EVALUATION
8 FURTHER WORK
9 CONCLUSION
10 REFERENCES
10.1 BOOKS
10.2 ARTICLES
10.3 WEBPAGES
Author: Christian Ewö
Source: Blekinge Institute of Technology
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