The Profitability of Moving Average Trading Strategies in the Thailand SET50 Index: Past and Future

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Rujira Chaysiri
Sucha Boontaricponpun
Piraya Sujjavanich
Kornchanok Ua-ampon

Abstract

          Technical analysis is one of the most popular methods that some investors believe can generate profit from stock markets. However, there is no consensus that technical analysis strategies can always make profits in different asset conditions. This study focuses on finding whether moving average trading strategies can outperform the buy and hold strategy in particular asset conditions. These asset conditions are constructed from the volatility and volume of a trading period of a stock in the Thailand SET50 index. In addition, this study forecasts the asset conditions of a stock for the next period by comparing the logistic regression and artificial neural network, to make the technical trading strategies useful in practice. The results show that the moving average trading strategies outperforms the buy and hold strategy in one asset condition. For forecasting the results of an asset condition, an artificial neural network has a higher accuracy rate than logistic regression for predicting asset conditions.

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