I've heard it said that "cointegration" analysis has replaced correlation analysis in many financial communities.
Does somebody have a clear and concise argument for the switch?
How about a software package that does this??
Thanks in advance
FT
Cointegration vs correlation
-
- Full Member
- Posts: 13
- Joined: Mon Dec 06, 2004 2:49 pm
Do a google on cointegration and financial.
A definition can be found at http://economics.about.com/library/glos ... ration.htm and I would reproduce it if I understood it.
A definition can be found at http://economics.about.com/library/glos ... ration.htm and I would reproduce it if I understood it.
Paul Wilmott didn't think "cointegration" was important enough to include in his book http://www.amazon.com/exec/obidos/tg/de ... 471498629/
Cointegration seems to be a binary indicator: a vector of time series are cointegrated, or they aren't. It doesn't sound all that useful to me but then I'm a practitioner not an academic.
Cointegration seems to be a binary indicator: a vector of time series are cointegrated, or they aren't. It doesn't sound all that useful to me but then I'm a practitioner not an academic.
Related?
One can google around and find a number of interesting papers, most of them econometric, and many of them directly related to markets (e.g. currencies, metals, interest rates, ags). The CATS and RATS software pops up in a number of papers and places, as do some other implementations and algorithms. The most accessible application seems to be building non-cointegrated portfolios (in comparison to non-correlated portfolios). I also found a few cautionary findings that some of the cointegration algorithms can fail to either establish cointegration when it exists, or mis-identify cases where it doesn't. I don't know enough about the field to discern the issues.
What I did find interesting is that a number of other trading ideas seem to pursue similar paths of differencing a price series and factoring for noise. (the focus of cointegration is on the consistency of residuals, or shape of noise as a result of the differences). For instance, a 2004 TASC article looked at trend identification using Q and B vectors. In particular, it seemed to do an excellent job to me of identifying the end of a trend (I thought it lagged to much at detecting onset of trend). So, that might be another application.
Cheers,
Kevin
What I did find interesting is that a number of other trading ideas seem to pursue similar paths of differencing a price series and factoring for noise. (the focus of cointegration is on the consistency of residuals, or shape of noise as a result of the differences). For instance, a 2004 TASC article looked at trend identification using Q and B vectors. In particular, it seemed to do an excellent job to me of identifying the end of a trend (I thought it lagged to much at detecting onset of trend). So, that might be another application.
Cheers,
Kevin