Matlab webinar on how to build trading rule or decision engine for market execution with genetic algorithm aka evolutionary learning

(Last Updated On: November 29, 2012)
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Matlab webinar on how to build trading rule or decision engine for market execution with genetic algorithm aka evolutionary learning

For 2010 webinar:

The files contained in this dowload were used in the webinar titled: Algorithmic Trading with MATLAB

Products for Financial Applications that originally aired on November 18, 2010. You can watch an

archived version of this webinar from and look for the title webinar.

It is recomended you watch this webinar as you walk through the code.

Here is I take away from this webinar:

1. Smart way to use trading rules and decisions to combine various strategies for executing market order. This genetic algorithm based on evolutionary learning. This is no different than using an equivalent of something like Streambase that I went on about a few weeks ago. This uses the best trading strategy based on a combination of trading signals.

2. Pay attention to when the author is visual building hist plots, he can automatically generate his Matlab code on the fly. This is same with his command history. Watch as well how he add comments to generate HTML reports when he published from the Matlab editor.

3. For any strategy development, you want to use 80% of the data set for testing and the rest for validation.

4. AT 19:26, check out the parameter sweep capabilities to calculate optimal lag among all your moving average parameters of the test set. At 20:31, you can use a 3d surface plot  to chart optimal lagging indicators with maximum Sharpe ratio.

5. At 40:22, learn how genetic programming can be used to combine various strategies together to get optimal returns. You basically combine different trading signals which are really different states of the market. You can view Genetic Programming in Financial Applications webinar for details. Bit stream representation is explained at 42:00 approximately.

6. 57:00 explains application of HFT with 58:00 explaining GPU and CUDA. Or you could use Embedded Matlab or Matlab compiler explained at 59:00. Simulink could be used as well which is visual. This targets FPGA to export C code from that. There is a 2009 Algorithmic Trading webinar that demonstrates the use of Simulink as well.


NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!
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About caustic

Hi i there My name is Bryan Downing. I am part of a company called QuantLabs.Net This is specifically a company with a high profile blog about technology, trading, financial, investment, quant, etc. It posts things on how to do job interviews with large companies like Morgan Stanley, Bloomberg, Citibank, and IBM. It also posts different unique tips and tricks on Java, C++, or C programming. It posts about different techniques in learning about Matlab and building models or strategies. There is a lot here if you are into venturing into the financial world like quant or technical analysis. It also discusses the future generation of trading and programming Specialties: C++, Java, C#, Matlab, quant, models, strategies, technical analysis, linux, windows P.S. I have been known to be the worst typist. Do not be offended by it as I like to bang stuff out and put priorty of what I do over typing. Maybe one day I can get a full time copy editor to help out. Do note I prefer videos as they are much easier to produce so check out my many video at