Does Averaging-In Work? Case Studies by - Ron Schoenberg and Al Corwin

Does Averaging-In Work? Case Studies by - Ron Schoenberg and Al Corwin


Ron Schoenberg and Al Corwin recently did some interesting research on the trading technique of "averaging-in". For e.g.: Let's say you have Rs4 to invest. If a future's price recently drops to Rs 2, though you expect it to eventually revert to Rs 3. Should you

A) buy 1 contract at Rs 2, and wait for the price to possibly drop to Rs 1 and then buy 2 more contracts (i.e. averaging-in); or
B) buy 2 contracts at Rs 2 each; or
C) wait to possibly buy 4 contracts at Rs 1 each?

Let's assume that the probability of the price dropping to Rs 1 once you have reached Rs 2 is p. It is easy to see that the average profits of the 3 options are the following:
A) p*(1*Rs1+2*Rs 2) + (1-p)*(1*Rs 1)=1+4p;
B) 2; and
C) p4*Rs 2=8p.

Profit A is lower than C when p > 1/4, and profit A is lower than profit C when p > 1/4. Hence, whatever p is, either option B or C is more profitable than averaging in, and thus averaging-in can never be optimal.

From a backtest point of view, the Schoenberg-Corwin argument is impeccable, since we know what p is for the historical period. You might argue, however, that financial markets is not quite stationary, and in my example, if the historical value of p was less than 1/4, it is quite possible that the future value can be more than 1/4. This is why I never make too much effort to optimize parameters in general, and I can sympathize with traders who insist on averaging-in even in the face of this solid piece of research!