What is it Based On?

Builder constructs trading strategies using a genetic programming algorithm to select different combinations of technical indicators, operators, and entry and exit orders. Builder includes technical indicators for trend, trend strength, oscillators, volatility, volume, time of day, day of week, and price patterns. The indicators are combined using logical and inequality operators. In addition, there are three different types of entry orders and six different types of exit orders. With all the possible combinations of rules and orders, Builder is capable of generating literally trillions of different possible trading strategies.

Builder incorporates several features that help guide the process to strategies that are likely to have good out-of-sample and real-time performance. In particular, Builder includes automatic out-of-sample testing, so you can separate the data on which the strategies are built ("in-sample" data) from the data used for testing ("out-of-sample" data). Also, you can choose to optimize for statistical significance, maximize the number of trades, and minimize the system complexity, all of which will increase the quality of the generated strategies. Moreover, the strategy logic produced by Builder incorporates volatility-normalized parameters, which help adapt the strategies to different market conditions. The user's guide includes a section that covers factors affecting out-of-sample performance and ways to maximize the out-of-sample and real-time trading results.

To build a strategy, all you need to do is select a file of price data, which you can save from a price chart, make a few settings to guide the build process, and press the Build button. The program does the rest. The generated strategy code is displayed in the code window, where you can copy the open code to your trading platform.

“First off I wanted to say how helpful Builder has been to me. I have been using it for a couple of years (with tradestation) and nearly all of the strategies have been profitable in real life.”
J. W., Sevenoaks, UK