Forum Discussion
Matrix Multiplication
- 4 years ago
I think I've got it and it's simpler than I initially anticipated.
Matrix Product = VAR _C1 = SELECTEDVALUE ( H1_CurrencyList[C1] ) VAR _C2 = SELECTEDVALUE ( H2_CurrencyList[C2] ) VAR _Matrix_ = ADDCOLUMNS ( ALL ( H1_CurrencyList[C1] ), "Row_1", VAR _C = H1_CurrencyList[C1] RETURN CALCULATE ( [Covariance], H1_CurrencyList[C1] = _C1, H2_CurrencyList[C2] = _C ), "Col_2", VAR _C = H1_CurrencyList[C1] RETURN CALCULATE ( [Cross Weights], H1_CurrencyList[C1] = _C, H2_CurrencyList[C2] = _C2 ) ) RETURN SUMX ( _Matrix_, [Row_1] * [Col_2] )Having a square matrix that's a cross product of a list of currencies with itself gives a nice solution that only requires one evaluation each of [Covariance] and [Cross Weights] per currency per cell in the result matrix (each of the N^2 result cells requires 2N measure calls for N currencies).
This is simpler than my comment on the gallery post I mentioned previously since I don't need to load the entire matrices, just the relevant row & column from each one. The main difficulty there is just setting up the indexing and filtering for the parts needed. The key logic in both is the same sum product.
What is your next step? What are you planning to do after the matrix multiplication?
Measures can use table variables during the computation process but the final result of a measure must be a scalar value.