By Michael Bryant Ph.D.
Abstract / Introduction:
One of the biggest trends in retail trading over the past decade has been the increase in the popularity of automated trading. In this type of trading, also known as automated order execution, buy and sell signals generated by a trading system are automatically executed by a platform connected to the trader’s brokerage account. This allows for hands-free trading, which enables faster execution, fewer errors, and the ability to trade shorter time frames with higher-frequency strategies.
As more and more traders have moved to automated trading, the interest in systematic trading strategies has increased. While some traders develop their own trading strategies, many traders lack the programming skills necessary to implement their ideas. Other traders lack the specific knowledge of technical trading methods or the experience required to design a viable strategy. Even for traders with the necessary skills for developing trading systems, the considerable time and effort required to develop a good strategy is often a deterrent.
A recently developed solution to this problem is the use of computer algorithms to automatically generate trading system code. The goal of this approach is to automate many
of the steps in the traditional process of developing trading systems. In the traditional, manual approach to strategy development, the trader selects elements of the trading strategy based on prior experience and knowledge of technical indicators, entry and exit order types, and strategy design. Commonly, a strategy is based on a market hypothesis; that is, an idea of how the market works. A viable trading strategy is typically developed through a long trialand-error process involving numerous iterations, revisions, and testing until acceptable results are achieved.