Trading rule discovery in the US stock market: An empirical study

This study develops a new template grid – rounding top and saucer – to detect buy signals. Most of the previous studies utilize historical data to derive the template grid, but do not clearly explain how to format weight values of the template grid. This makes the template a “black box” for users since it is difficult to infer the process of the template formation. Therefore, this study proposes a simple and explicit method for deriving the template grid. In addition, to more accurately detect buy signals, the trading rules are developed by capturing reversal of price trend. The empirical results indicate that the template grid and the proposed trading rules developed in this study have considerable forecasting power across tech stocks traded in the US, including MSFT, IBM, INTC, ORCL, DELL, APPLE and HP, since the average returns of the proposed trading rule are greater than the results of buying every day over the sample period. The method proposed here could therefore become an effective component of an expert system to assist investors in investment decisions.