Threshold-Adjusted Orb Strategies With Genetic Algorithm And Protective Closing Strategy On Taiwan Futures Market

Opening range breakout (ORB) is a well-known intraday trading strategy that generates trading signals through technical analysis; however, ORB does not make full use of market characteristics and does not define closing strategy. These problems make the ORB strategy not stable or robust enough. In this paper, we adjust thresholds through historical data to enhance profitability, and design protective closing strategy to prevent unacceptable losses. However, there are numerous parameters combinations, and the solution space is approximately 2^14. Therefore, we implement genetic algorithm to improve the efficiency and rationality of parameter selection. We found that the performance of the GAORB Sharpe with stop-loss mechanism is outstanding. The strategy we proposed can generate 9.303% annual return and 15.716% Sharpe ratio, which is 2.5% and 5% more than the original strategy, and cut the maximum drawdown by half. Further, it can save 90% of the computation by genetic algorithm. In summary, we recommend adjusting the threshold and implementing stop-loss mechanism to the ORB strategy, and selecting parameters through genetic algorithms to improve overall performance.