There is a model which is based on N factors which are correlated through a correlation matrix of size NxN. For a subset of M factors the corresponding values are explicitly given over a specific time period [A,B].
Which methods are recommended to obtain the most appropriate "missing" values for remaining N-M factors over that time period [A,B]?
The problem is a little different compared to "imputing missing values for a time series", since these missing values have to be consistent with a given correlation matrix.
I am looking at various alternatives, and any relevant reference would be appreciated.
On a side note, a promising avenue (with some enhancements needed) is 2013 the article "How to Combine Long and Short Return Histories Efficiently" by S. Page