Basically, you'd send a portfolio (text is fine - all that's needed is the full name of all of the investments and dollar amounts), and a time frame, and you'll get a custom benchmark portfolio shell comprised of the best
available fitting indices for each asset class back, with returns looking back over any time frame (as long as the data goes back).
Not exact matches
Following Roy's recipe, you can get a reasonable - looking
fit to data with very little fine - tuning because Roy has given himself a lot of elbow room to play around in: you have the choice of any two variability
indices among dozens
available, you make an arbitrary linear combination of them to suit your purposes, you choose whatever mixed layer depth you want, and you finish it all off by allowing yourself the luxury of diddling the initial condition.
One should possess sound knowledge in the various methods of production
available for a component and the ability to make decisions to choose the one which best
fits into the purpose with maximized profits and enhanced customer satisfaction
index.
The model chi - square is the only model
fit statistic
available when modeling growth in binary observed variables, and this
index suggested that our model provided a good
fit to the data, χ 2 (25) = 29.10, p > 0.05.