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Explore the research behind our trading, plus some just-for-fun stuff....

Posted on Dec 03, 2015 by Kris Longmore
29 comments.
9,262 Views

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. I'm a big fan of Ernie's work and have used his material as inspiration for a great deal of my own research. My...

Posted on Nov 24, 2015 by Kris Longmore
5 comments.
554 Views

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...

Posted on Nov 15, 2015 by Kris Longmore
22 comments.
2,340 Views

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 useful and practical to real trading. I'll initially try two approaches: Investigate whether there are...

Posted on Nov 10, 2015 by Kris Longmore
18 comments.
7,573 Views

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 applicable to modern financial markets. Today, he has a fancy website...

Posted on Oct 30, 2015 by Kris Longmore
5 comments.
433 Views

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 second example, where an allowance is made for the drawdown...

Posted on Oct 27, 2015 by Kris Longmore
3 comments.
656 Views

In the first part of this article, I described a procedure for empirically testing whether a trading strategy has predictive power by comparing its performance to the distribution of the performance of a large number of random strategies with similar trade distributions. In this post, I will present the results of the simple example described by the code in the previous...

Posted on Oct 18, 2015 by Kris Longmore
7 comments.
1,153 Views

Picture this: A developer has coded up a brilliant strategy, taking great care not to over-optimize. There is no look-ahead bias and the developer has accounted for data-mining bias. The out of sample backtest looks great. Is it time to go live?    I would've said yes, until I read Ernie Chan's Algorithmic Trading and realised that I hadn't adequately accounted...

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