These issues are usually overlooked in previous studies. We also investigate the performances of technical trading rules with optimized parameters compared to those from standard parameters. In addition, we study the odds of profitable or unprofitable trades and the associated returns. 2013), this paper focuses on popular technical indicators reported in the media and applied in actual markets by technical analysts. Instead of focusing on moving average rules or trading range breakout rules like in previous research (e.g. This study revisits this important issue by expanding the scope of trading rules. However, they find that transaction costs can eliminate trading profits in most markets, except Thailand. ( 2013) also find that technical trading rules have predictive power particularly in emerging markets of Malaysia, Thailand, Indonesia, and the Philippines but to a much lower extent in a more mature market of Singapore. The case of Southeast Asian stock market is interesting since both Bessembinder and Chan ( 1998) and Ratner and Leal ( 1999) find that trading rules are successful in predicting stock price movement in Southeast Asian markets. Therefore, the question of whether technical trading rules can consistently generate profits becomes an empirical issue concerning efficiency of actual markets. If investors could make money from applying these trading rules, this would indicate that the market is inefficient. As technical analysis uses only current and past trading data, it is not possible to obtain abnormal positive returns by applying these technical trading rules. The EMH states that all available and relevant information are already incorporated in security prices.

Unfortunately, according to the efficient market hypothesis (EMH), this endeavor is ultimately futile. It aims to establish buying and selling rules that maximize profits and still control risks of loss. Technical analysis involves making investment decisions based on past trading data. They make money from having a higher average profit from profitable trades than an average loss from unprofitable ones. Thirdly, even profitable strategies could not reliably predict subsequent market directions. Secondly, technical trading rules can be beneficial to individual investors as they help them to counter the behavioral bias called disposition effects which is the tendency to sell winning stocks too soon and holding on to losing stocks too long. Basically, traders cannot expect to buy at a relative low price and sell at a relative high price by just using technical trading rules. Firstly, technical indicators does not help much in terms of market timing. This fact suggests different levels of market efficiency among Southeast Asian stock markets. However, after taking transaction costs into account, most technical trading rules do not generate net returns. The technical trading rules also generate statistical significant returns in the Malaysian, Indonesian and the Philippine markets. Our empirical results show a strong performance of technical trading rules in an emerging stock market of Thailand but not in a more mature stock market of Singapore. Performances are compared to a simple Buy-and-Hold. Trading strategies investigated include Relative Strength Index, Stochastic oscillator, Moving Average Convergence-Divergence, Directional Movement Indicator and On Balance Volume.

The instruments investigated are five Southeast Asian stock market indices: SET index (Thailand), FTSE Bursa Malaysia KLC index (Malaysia), FTSE Straits Times index (Singapore), JSX Composite index (Indonesia), and PSE composite index (the Philippines). The data cover a period of 14 years from January 2000 to December 2013.

This paper examines the profitability of technical trading rules in the five Southeast Asian stock markets.

Max trading system indicators