I have several assets, each with different return histories.
Some of the assets have 75 days of return history, others have 40 or so days. In calculating a robust covariance matrix, should I be using a resampling with replacement technique or should I be using an expectation maximization algorithm?
I was thinking of truncating the samples so that they all share ~40 days of return history, and then resampling that distribution of returns with replacement.
But, I'm not sure that's ideal.