Finding correlated or comoving stocks

I have a table of daily closing stock prices and commodity prices such as Gold, Oil, etc. I want to find what stocks move closely with another stock or a commodity.

Where do I start to do this type of analysis - I know java, SQL, python, perl, and a lit开发者_高级运维tle bit of R.

Willing to buy and learn new tools like Matlab if necessary.

Any guidance will be highly appreciated.

This is not a homework question.

Thanks..

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The technique you are looking for is called cointegration. Language is not important at all when computing cointegration of two time series so use whatever you are comfortable with.

I disagree with other responses that computation is not a problem. It is a huge problem to be able to compute potentially billions of cointegration coefficients between different time series. Using a highly optimized library is critical. However this article on cointegration testing in R should get you started.

Also checkout quant.stackexchange.com for more info on quantitative finance.

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Try this:

http://www.sectorspdr.com/correlation/

http://www.etfscreen.com/corr.php

http://correlate.googlelabs.com/faq

https://quant.stackexchange.com/questions/1027/correlation-and-cointegration-similarities-differences-relationships/1038#1038

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Where do I start to do this type of analysis

If I were you, I'd start by searching Google Scholar for the word "comovement". Not everything that turns up is directly relevant, but there's quite a lot of stuff that is relevant.

By looking through the papers and googling some more, you should get a clearer picture of what types of statistical methods to learn.

I agree with Ben Bolker that computational tools are not the main issue at this point.