TUTORIAL Trading For Future Work

We have applied a data mining approach to analyse and predict the trend of the stock price and applied it
in real stock trading practice. Results have shown that the proposed methodology improves the trading performance over some existing strategies in some cases.

Success with Trading

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 While the methodology developed in the work can correctly predict the trend of stock prices for some countries, it is not able to predict well for all. The stock price is very volatile in nature. The proposed trend prediction approach certainly has its limitations. The following future work may improve the performance of the method.

1. A simple decision on classificationin the future.

2. Improve the computation efficiency by using sophisticated and scalable clustering techniques, such as [4,8].

3. Introducing scale change of clusters is made using the linear regression model in the present work. We can further improve the accuracy of the trend prediction by using fuzzy or probabilistic decision systems to pattern matching can discover similar patterns with different time scales.

4. Combine our method with other techniques, such as GP, for better and more sophisticated trading strategies.

Acknowledgements

The authors acknowledge Damien McAullay and Arun Vishwanath for their assistance in the preparation of the paper.