Lately, I was skimming through a book
The New Money Management by Ralph Vince (1995). He says that the optimal
f depends on the number of trials (and asymptotically approaches the kelly
f).
He's maximizing something he calls "expected average compound growth" (EACG). He uses an example of a 50/50 coin with 2:1 payout.
If we're going to quit after:
1 flip, the f is 1.
2 flips, the f is 0.5
3 flips, the f is .37868
4 flips, f = .33626
...
8 flips, f=.2871
...
infinity flips, f = .25 (kelly bet)
That table is on page 80. I don't understand how he got those numbers or how they're justified. Anyone know?
I can see why f would vary with #flips. If you're only playing 1 flip, it's meaningless to talk about exponential growth. With a few flips, you want to make the most of your finite-time opportunity, hence be a little more aggressive than kelly.
In practice, the f approaches kelly pretty quickly, so knowing the finite-time f might not be useful. Still interesting though.
Edit: then on p. 81 he says:
Quote:
...I strongly feel that if an investor's utility function is other than ln x, the markets, and investing in general, are poor places to deal with this or to try to maximize one's utility....In short, the markets are a bad place to find out you are not a wealth maximizer. The psychiatrist's couch may be a more gentle environment in which to deal with that.
would you guys agree?
Last edited by heehaww; 05-17-2014 at 10:55 AM.