Better trading by design

摘要

Input values can make or break a trading system. The accurate setting ofrnthese variables is critical, but it can require Institutional-level computing power. The Design of Experiments method optimization technique doesn't require the computational horsepower that traditional methods demand.rnAutomated trading systems. especially those based on technical indicators, are all the rage. Such systems are highly dependent on settings, such as moving average periods, which are usually determined in unsystematic fashion. Some are set by tradition, such as only going long when an index is above a 200-day moving average. Others are found by brute-force backtesting, generally by what is called "single-factor design," in which each setting is tested on its own.