Consider the data set below. The blue is the SP500 futures trading 24h/day. The other is the VIX which I only have values for 7h/day. Obviously both are somewhat inversely correlated.
What method would you recommend for filling the hidden/missing orange VIX points with 'most likely' values, given the observed correlation structure and boundary conditions? I've considered iterative mutlivariate singular spectrum analysis, but this is cumbersome.
Any help welcome.