selection bias

Posted on Nov 24, 2015 by Kris Longmore
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Important preface: This post is in no way intended to showcase a particular trading strategy. It is purely to share and demonstrate the use of the framework I've put together to speed the research and development process for a particular type of trading strategy. Comments and critiques regarding the framework and the methodology used are most welcome. Backtest results presented are for illustrating the methodology and describing the outputs only. That done, on to the interesting stuff My last two posts (Part 1 here and Part 2 here) explored applying the k-means clustering algorithm for unsupervised discovery of candlestick patterns. The results were interesting enough (to me at least) to justify further research in this domain, but nothing presented thus far would be of much use in a standalone trading system. There are many possible directions in which this research could go. Some ideas that could be worth pursuing include: Providing the clustering algorithm with other data, such as trend or volatility information; Extending the search to include two- and three-day patterns; Varying the number of clusters; Searching across markets and asset...