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..

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.

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

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.