“Our strategy does beat the market by about 50% over 15 years though ”

Oh no, no, NO!

Those who search they, will find!

If you search through a lot of series then you will find some relations. That does not mean that they will remain or be stable.

Do you remember that something happened 2007-2008?

Do an Chow-test before 2007 and after 2008 and check if the parameters are the same? Of course they will not.

Do you believe that the “beta” is a fixed parameter? Obviously you don't since you use a “rolling panel OLS”. Maybe that can work like some smoothing or a crude Kalman filter. But I don't think that it will work. In a year like 2008 all of these betas might have flipped.

I think that Bugmans “nightmare data set” in the environmetrics area is much easier than the data in your area.

Now I think that you should do a stochastic specification of the data in your area, with multicolinearity, errors in variables, interdependent systems, the problems mentioned above, omitted variables, varying distributed lag models and many other problems and then ask someone about these problems.

You could ask Dason, who above asked you for clarification. Ask him – today – something like under what conditions with the above stochastic specification will a Kalman filter work? (I believe that someone is having a time series exam today!)

But derksheng, (you are a nice person and) I believe that you will learn a lot of statistics on this and hopefully not lose any money. The only profitable with this is to do education about it.