Using AdaBoost for Taiwan Stock Index Future Intra-day Trading System
Date Issued
2008
Date
2008
Author(s)
Lin, Tien-Nan
Abstract
We use AdaBoost for the Taiwan stock index future intra-day trading system. We design a trading system which can trade futures contracts automatically according to real-time streaming quotes. In addition, it allows us to use historical data for back testing and then examines the performance of our trading strategies.he training data are 1 minute candlesticks from 2004 to 2007. The period of testing starts from January 2008 and ends in June 2008. AdaBoost is an excellent machine learning technique for solving pattern classification problems. We train bull and bear classifiers by AdaBoost. These two kinds of classifiers support our trading system to find the proper time to long or short futures contract. In this thesis we provide low risk and steady profit models for futures traders.
Subjects
AdaBoost
Taiwan stock index future
Technical index
Programming trading
Intra day trading
Machine learning
Pattern classification
Type
thesis
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