Consider the following problem:
- You would like to understand how a particular Multi Asset Class fund is invested (ascertain the weights attributed to each asset class)
- You have at your disposal a series of daily returns for that fund
- You also have daily returns for broad asset classes (Gov Bond index, local equities, foreign equities, High Yield, ...)
- Crucially, you don't know in which of those asset classes the fund is invested in (could be only a subset of these or worse, could be in an asset class outside the set)
How would I go about determining how the fund has been invested: - On average over the entire period - On a rolling window basis
And how might I determine if the fund is invested in assets not in the above set?
My thoughts on the matter:
- I could use rolling regressions on the daily returns, excluding an intercept term (the CASH asset class would act like my constant anyway).
- From that regression, the coefficients would be my weights and the error term would provide clues as to whether the model specification is lacking any asset classes
- An issue with this approach might be the unreliability of the coefficients if two or more asset classes are highly cointegrated (eg: Small and large cap equities or AAA and AA rated bonds)
I've looked far and wide, but I haven't been able to find a single source that looks at this particular problem. If someone can point me in the right direction, I would be very appreciative.
Thank you for your help and insight!
