Cool PCA analysis framework with neural network done in Matlab

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*TRADING ALERTS*Cool PCA analysis framework with neural network done in Matlab

Many examples of PCA uses in finance with Matlab source code. There are some examples use with Value at Risk applications.

Lots of examples here:

http://quant.stackexchange.com/questions/1020/equity-risk-model-using-pca <– See the answer by vonjd

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1358533 <– Meucci paper with example code at http://www.mathworks.com/matlabcentral/ﬁleexchange/23271 also focus on portfolio

http://www.cs.princeton.edu/picasso/mats/PCA-Tutorial-Intuition_jp.pdf <– uses toy example so not useful

http://stackoverflow.com/questions/21242542/principal-components-calculated-using-different-functions-in-matlab <– good example how to use princomp

http://www.docstoc.com/docs/20298522/MATLAB-CODE-FOR-PCA <– little example with no explanation

http://www.mathfinance.cn/category/matlab/1/3/ –> Suggested another PCA framework at

http://www.nlpca.org/matlab.html –> this is an non linear PCA framework

http://books.google.ca/books?id=AxvgfuSedRAC&pg=PA302&lpg=PA302&dq=matlab+pca+finance&source=bl&ots=b_k8uf-abe&sig=8svs1dUkKvRhJf1y4Rbm_TpLBPw&hl=en&sa=X&ei=lqdOU8zVC4Si2AWMwIDABA&ved=0CEoQ6AEwAzgK#v=onepage&q=matlab%20pca%20finance&f=false <– This has an exact example in this paid book Stochastic Simulation and Applications in Finance with MATLAB Programs

http://en.wikipedia.org/wiki/Principal_component_analysis

http://www.quantatrisk.com/tag/matlab/ <— good explanation of PCA with real world example and source code Best Example headline of (heatmap and different plots!)

http://www.di.ens.fr/~aspremon/PDF/INFORMS05sparsePCA.pdf <– no source code examples

http://www.mathworks.com/com/help/stats/princomp.html <— nice explanation from Mathworks of core function

http://matlab-trading.blogspot.ca/2012/12/using-pca-for-spread-trading.html –> spread trading with detailed description from http://www.cs.bham.ac.uk/~pxt/IDA/PCA.tutorial.pdf with code but not compatible with Matlab

http://www.jasonhsu.org/uploads/1/0/0/7/10075125/principal_components_analysis2.pdf <– no link to the source code

http://www.quantzone.org/?tag=pca –> refers to nlpca framework above

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Youtube video New Matlab 2013a enhancements in Stats with PCA FPGA and Simulink code generation to your C or C++ API

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HI there

The march to my high frequency trading system continues! I have listed below the latest accomplishments in the world of GPU, CUDA ,and Matlab. One major take away in all this is that if you choose C*UDA, you will be happy to develop the new CUDA 5 math library*. All in all, it is very powerful and mind blowingly fast!

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P.S. Tomorrow will be further secrets to be revealed about Matlab’s data analytical power.

FREE GPU CUDA 3rd party high level C++ library for math awesomeness with genetic algorithm, neural net learning, PCA, FFT, BLAS

I stlll have to verify this is free but there is a download button with no limitations. I will try to post a video on this.

Key is ensure it is compatible for both Windows and Linux which this does

http://www.accelereyes.com/arrayfire/c/examples_2financial_2blackscholes_8cpp-example.htm

After further digging, this is actually an expensive option:

http://www.accelereyes.com/products/arrayfire_licensing

**Learn more if I implement this into HFT platform**

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This has been posted in the **PremiumMembership section**. This saves people tonnes of time which R script works and which ones don’t. Also, there will be a R source code walkthrough of each coming over the next few weeks.

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Youtube video request Seeking PCA, Markov, data mining examples for automated trading model profits

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I am curious if anyone has had success applying principal component analysis in the context of alpha generation (and not in the context of risk, as PCA is typically applied). For instance, I like the straightforward “absorption ratio” introduced by Kritzman, et al. here:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1633027

I suspect that tracking the evolution of portfolio risk concentration may yield forward-looking clues on the portfolio’s performance. For instance, perhaps a factor mimicking portfolio may lose efficacy if its risk becomes highly concentrated during the life of the trade (in this hypothetical context, the “absorption ratio” is used as a timing parameter for factor rotation).

As an aside, outside of alpha generation, I think any “real-time” systemic risk metrics are highly relevant in today’s market. Particularly in the US equity space, where investors have enjoyed a respite (of sorts) from macro-driven Eurozone news since mid-Dec (coinciding with the ECB’s 3-yr LTRO announcement). The abrupt declines over the last hour of trading on May 22 (purportedly driven by comments from the former Greece PM regarding the country’s potential exit from the euro) is a sharp reminder to me just how quickly the market can switch back to the high correlation environments of 2H11. Monitoring systematic risk may give active investors sufficient time to adjust their level of activeness/leverage in open positions.