This paper presents a study of technical analysis trading rules that generate abnormal returns for futures prices. It reports abnormal returns over and above that generated by the passive buy-and-hold policy for FKLI, FCPO, Soyoil, Soybean and Corn futures for the periods tested. This research devises a new technical analysis trading model, Bollinger Bands Z-Test (BBZ), using standard deviation. It proposes that BBZ attempts to capture large price movements which happen beyond 1 standard deviation. The mechanical buy signal is above +1 standard deviation and sell signal is below –1 standard deviation. For the period 12/15/1995-12/31/2008, BBZ yields a return of 1,048.6 points for FKLI in comparison to the passive buy-and-hold policy which yields a negative return of –110.5 points. The returns obtained using optimized BBZ for FCPO, Soyoil, Soybean and Corn futures for the year 2008 are 1,119, 27, 522 and 328 points respectively.

Technical analysis is the study of price patterns to identify trading opportunities. It is an analysis of historical price data to identify price trends. Technical analysis is an emerging science because quantitative methods for evaluating price movement to make trading decisions have now become a dominant part of current market analysis (Kaufman, 1998). Detecting new trends early using mechanical trading rules in technical analysis is one of the techniques that professional traders use to make abnormal returns above the benchmark return of the passive buy-and-hold policy.

In many large financial institutions, some professional traders depend entirely on technical analysis and mechanical technical trading systems to trade in financial instruments. Taylor and Allen (1992) find in their survey of chief foreign exchange dealers based in London that more than half of the respondents place some importance on technical analysis. This study can therefore be used by market professionals to understand and apply the trading techniques contained herein, to systematically outperform the benchmark return of the passive buy-and-hold policy.

This study reports the test results which show abnormal returns above the benchmark return of the passive buy-and-hold policy. By using mechanical technical trading rules to detect new trends early, generating abnormal returns, in excess of those generated by the passive buy-and-hold policy, is possible. This study is based on the insights of Mandelbrot and Hudson's (2004) proof that market is not random. This view is opposite to Fama's (1965) random-walk theory. Mandelbrot and Hudson observe that markets are ruled by power curves, and not normal probability curves, and that long-term dependence of sequential price action exists.

Financial Risk Management Journal, Future Prices, Technical Analysis, Mechanical Trading Rules, Financial Instruments, Mechanical Technical Trading Systems, Standard Trading Systems, Simple Moving Average, Algorithm Trading System, Model Trading Desks.