Math Trading

I have the feeling that there is some subtle yet spread misconception about data-driven research in financial markets and I will take this article: Seeking Alpha – Not Even Wrong: Why Data-Mine...

https://mathtrading.wordpress.com/2014/09/14/in-defense-of-a-quantitative-approach-to-financial-markets/

In today’s markets dominated by High-Frequency algos, room for profits for non-HF (and more importantly, non-HF aware) guys is generally speaking reduced. The proportional performance impact of...

https://mathtrading.wordpress.com/2014/04/21/order-matching-algorithms/

Lately I have been looking for a more systematic way to get around overfitting and in my quest I found it useful to borrow some techniques from the Machine Learning field. If you think about it, ...

https://mathtrading.wordpress.com/2014/01/16/features-selection-in-trading-algorithms/

This is a quick follow-up on my previous post on Quantile normalization. Instead of removing just the top X quantile of returns/trades when optimizing a strategy’s parameters space, my recent a...

https://mathtrading.wordpress.com/2013/10/25/trimmed-performance-estimators/

While overfitting is certainly a challenge, falling for the opposite extreme is also a possibility. Reporting part of an interview of William Echkardt from Futures magazine (which I would recomme...

https://mathtrading.wordpress.com/2013/09/22/underfitting-misfitting-and-understanding-alphas-drivers/

In one way or another, trading is mainly about predicting the future from the past and the main question is to know how likely our bet is to be successful.  To try to answer this question withou...

https://mathtrading.wordpress.com/2013/07/05/overfitting-forecasting-and-trading/

A couple of days ago I was reflecting on what the moving average of a price really is. The idea stemmed from the consideration that any price can be expressed as a starting price plus the sum of ...

https://mathtrading.wordpress.com/2013/03/02/we-dont-quite-know-what-moving-averages-are/

When trying to analyse market data it is common practice to use techniques borrowed from different fields to transform the data. Examples of these are probability distributions of price returns, ...

https://mathtrading.wordpress.com/2013/01/03/defining-a-market-vs-characterizing-a-market/

To understand whether a strategy is able to perform in the future, the first question to ask is probably whether our strategy really showed great performance in the historic back-test or all it ...

https://mathtrading.wordpress.com/2012/12/16/quantile-normalization-a-simple-trick-to-reduce-overfitting/

Without exaggeration, diversification is one of the most powerful tools of a trader, allowing to enhance many characteristics of a system with relatively little effort. However, as with many thin...

https://mathtrading.wordpress.com/2012/11/25/perils-and-rewards-of-diversification-improve-your-systems-sharpe/