Quote from Rationalize:
That's pretty interesting. I am curious as to whether there are certain patterns in the change-in-correlation that could lead that system to chase itself somewhat?
Searching recurring patterns that anticipate the future behavior of a system, by studiing the changes in its levels of correlation inside the entire portfolio and its drawdwon levels compared to the performances of other systems, is a very complicated task that could possibly be resolved through sophisticated machine learning techniques.
By my small experience I can say that, if these patterns exist, they are very difficult to find. In fact is not always the case that when a trend following system outperforms on a certain symbol, then a mean reversion system must outperform on a symbol uncorrelated to the first, or even that a trend following system applied on a highly correlated symbol to the first must outperforms too.
I think this difficult exists because in a portfolio composed by several strategies applied to different symbols, the changes measured on correlation level of their returns and the changes obtained in their net performances usually not have the same speed.
In practice the levels of correlation of strategies returns traded on different symbols do not explain the changes occurred in the price bias of the symbols traded, and so on cannot explain their future performances.
What I do is to adapt the systems market exposition measuring both their last performance (its drawdown level) and their behaviour inside the entire portfolio (its mean correlation level vs all others used systems), minimizing exposure or stopping the unsafe systems and maximizing overperforming and uncorrelated systems.
Maybe this method suffer a certain delay, by since now it has done its dirty work with good returns and lower drawdowns.
My 2 cents..