Bill,
Rather than put up the entire PDF, maybe better if I just illustrate the basic idea here for the sake of perpetuating the thread (admittedly, I don't understand why you say the problem is solvable with mean-variance here, unless I am entirely misunderstanding the problem)
Let's say we have a guy who can only reallocate once a month, and he wants to be expected growth optimal at the end of the quarter. Let's further stipulate he is engaged in only a single "contest" that pays 2:1 with p=.5 (so that the answer to the Kelly Criterion equals what would be the optimal fraction to trade, an instance I refer to as the 'Special Case' where that holds).
Asymptotically, .25 is the optimal fraction, but at at horizon of 3 events, it is expected suboptimal. Clearly, in a contest with a positive expectation (probability-weighted mean of potential outcomes) where the horizon is only 1 outcome, the expected growth-optimal fraction is always 1. As the number of plays increases, approaching infinity, the asymptote of .25 is approached (but is never the expected growth optimal fraction, but rather a limit to it).
In fact, at 3 plays the expected growth-optimal fraction to wager on each of the three consecutive contests is .37868 as it turns out. I have attached a graph of this (hope this comes through) showing the expected growth values versus fraction wagered for horizons of 1 to 8 consecutive contests. Not only does the peak migrate towards the asymptotic peak, from 1 to .25 in this particular game, but the character of the curve changes (e.g. eventually inflection points appear, etc.).
Isn't this exactly the kind of thing we are discussing in this thread, or am I way off here? -Ralph Vince
Rather than put up the entire PDF, maybe better if I just illustrate the basic idea here for the sake of perpetuating the thread (admittedly, I don't understand why you say the problem is solvable with mean-variance here, unless I am entirely misunderstanding the problem)
Let's say we have a guy who can only reallocate once a month, and he wants to be expected growth optimal at the end of the quarter. Let's further stipulate he is engaged in only a single "contest" that pays 2:1 with p=.5 (so that the answer to the Kelly Criterion equals what would be the optimal fraction to trade, an instance I refer to as the 'Special Case' where that holds).
Asymptotically, .25 is the optimal fraction, but at at horizon of 3 events, it is expected suboptimal. Clearly, in a contest with a positive expectation (probability-weighted mean of potential outcomes) where the horizon is only 1 outcome, the expected growth-optimal fraction is always 1. As the number of plays increases, approaching infinity, the asymptote of .25 is approached (but is never the expected growth optimal fraction, but rather a limit to it).
In fact, at 3 plays the expected growth-optimal fraction to wager on each of the three consecutive contests is .37868 as it turns out. I have attached a graph of this (hope this comes through) showing the expected growth values versus fraction wagered for horizons of 1 to 8 consecutive contests. Not only does the peak migrate towards the asymptotic peak, from 1 to .25 in this particular game, but the character of the curve changes (e.g. eventually inflection points appear, etc.).
Isn't this exactly the kind of thing we are discussing in this thread, or am I way off here? -Ralph Vince