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Testing and Analysis of Algorithmic Trading Strategies in MATLAB – Problems and Solutions (Part 1)

Tuesday, November 29, 2016 2:45
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(Before It's News)

Hello, my name is Igor Volkov, I have been developing algorithmic trading strategies since 2006 and have worked in several hedge funds. In this article, I would like to discuss difficulties arising on the way of MATLAB trading strategies developer during testing and analysis, as well as to offer possible solutions.

I have been using MATLAB for testing of algorithm strategies since 2007 and I have come to conclusion that this is not only the most convenient research tool, but also the most powerful one because it makes possible using of complex statistical and econometric models, neural networks, machine learning, digital filters, fuzzy logic, etc by adding toolbox. The MATLAB language is quite simple and well documented, so even a non-programmer (like me) can master it.

How It All Started…
It was 2008 (if I am not mistaken) when the first webinar on algorithmic trading in MATLAB with Ali Kazaam was released, covering the topic of optimising simple strategies based on technical indicators, etc. in spite of a rather “chaotic” code, tools were interesting enough to use. They served as a starting point for research and enhancement of a testing and analysis model which would allow to use all the power of toolboxes and freedom of MATLAB actions during creation of one’s own trade strategies, at the same time it would allow to control the process of testing and the obtained data and their subsequent analysis would choose effective portfolio of robust trading systems.

Subsequently, Mathworks webinars have been updated every year and gradually introduced more and more interesting elements. Thus, the first webinar on pairs trading (statistical arbitrage) using the Econometric Toolbox was held in 2010, although the Toolbox of testing and analysis remained the same.

In 2013, Trading Toolbox from Mathworks appeared which allowed to connect MATLAB to different brokers for execution of their applications. Although there were automatic solutions for execution of the transactions, from that point MATLAB could be considered a system for developing trading strategies with a full cycle: from data loading to the execution of automated trading strategies.

Why Should Every Algotrader Reinvent the Wheel?
However, Mathworks has not offered a complete solution for testing and analysis of the strategies – those codes that you could get out of webinars were the only “elements” of a full system test, and it was necessary to modify them, customise them, and add them to the GUI for ease of use. It was very time consuming, thus posing a question: whatever the strategy was, it must go through the same process of testing and analysis, which would allow it to be classified as stable and usable – so why should every algotrader reinvent the wheel and write his/her own code for proper testing strategies in MATLAB?

So the decision was made to create a product that would allow to perform the whole process associated with the testing and analysis of algorithmic trading strategies using a simple and user-friendly interface. 

B4INREMOTE-aHR0cHM6Ly80LmJwLmJsb2dzcG90LmNvbS8ta3dJcm00UTQxMjAvV0QwWEpib2hiVUkvQUFBQUFBQUFBSlkvOW95MGNaRWRRaG91UFVOSHhWdGdHdFo3TU5lWE9kN3NRQ0xjQi9zNjQwL0dJRi1BcnRpY2xlLU9wdDMuZ2lm
WFAToolbox – Walk-Forward Analysis Toolbox for MATLAB®

We  decided to call the solution WFAToolbox – Walk-Forward Analysis Toolbox which demo version has been available on http://wfatoolbox.com since 2013.

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