Quant Mashup - Robot Wealth Exploring mean reversion and cointegration with Zorro and R: part 1 [Robot Wealth]This series of posts is inspired by several chapters from Ernie Chan’s highly recommended book Algorithmic Trading. The book follows Ernie’s first contribution, Quantitative Trading, and focuses on testing and implementing a number of strategies that exploit measurable market inefficiencies.(...) A framework for rapid and robust system development based on k-means clustering [Robot Wealth]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(...) Unsupervised candlestick classification for fun and profit – part 2 [Robot Wealth]In the last article, I described an application of the k-means clustering algorithm for classifying candlesticks based on the relative position of their open, high, low and close. This was a simple enough exercise, but now I tackle something more challenging: isolating information that is both(...) Unsupervised candlestick classification for fun and profit - part 1 [Robot Wealth]Candlestick patterns were used to trade the rice market in Japan back in the 1800's. Steve Nison popularised the idea in the western world and claims that the technique, which is based on the premise that the appearance of certain patterns portend the future direction of the market, is(...) The Financial Hacker’s Cold Blood Index [Robot Wealth]This post builds on work done by jcl over at his blog, The Financial Hacker. He proposes the Cold Blood Index as a means of objectively deciding whether to continue trading a system through a drawdown. I was recently looking for a solution like this and actually settled on a modification of jcl’s(...)