Trading systems come in two flavors: model-based and data-mining. This article deals with model based strategies. The algorithms are often astoundingly simple, but properly developing them has its difficulties and pitfalls (otherwise anyone would be doing it). Even a significant market inefficiency gives a system only a relatively small edge. A little mistake can turn a winning strategy into a losing one. And you will not necessarily see this in the backtest. Continue reading “Build Better Strategies! Part 2: Model-Based Systems”
Enough blog posts, papers, and books deal with how to properly optimize and test trading systems. But there is little information about how to get to such a system in the first place. The described strategies often seem to have appeared out of thin air. Does a trading system require some sort of epiphany? Or is there a systematic approach to developing it?
This post is the first of a small series in which I’ll attempt a methodical way to build trading strategies. The first part deals with the two main methods of strategy development, with market hypotheses and with a Swiss Franc case study. Continue reading “Build Better Strategies!”