Hot answers tagged correlation-matrix
Yes, you need Cholesky factorization. You can find the general idea here: http://www.goddardconsulting.ca/option-pricing-monte-carlo-basket.html Plus the implementation in MATLAB here: http://www.goddardconsulting.ca/matlab-monte-carlo-assetpaths-corr.html The code in general should be easily translatable. The only difficulty is the Cholesky factorization ...
I am not an expert in this field, but it would be best to consider a full multivariate GARCH model. This paper by Engle and Sheppard should be a good start. I think the constant correlation matrix approach is covered to a certain extent too. I hope this helps.
I had to answer because of your name, and becaue I deal with portfolio optimization often. In my world of equities correlation does matter a lot. If one follows the thoughts e.g. here then it matters most. I deal with minimum-variance construction (no expected return, of course some constraints on the weights) and there I often see positions that come ...
See "Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size" by Ledoit and Wolf. http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1031689018
How about an O(N log(n)) solution ? To be a viable trading strategy, you often expect them variances to be similar, so just calculate ordinary volatility and put it in an ordered array. Of course that's going to be period dependent, so pick a few arbitrary periods and see which instruments end up being together. Then you get clusters of vastly smaller ...
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