(THE KELLY CRITERION IN BLACKJACK SPORTS BETTING, AND THE STOCK MARKET1
where:
- f* is the fraction of the current bankroll to wager;
- b is the net odds received on the wager ("b to 1"); that is, you could win $b (plus the $1 wagered) for a $1 bet
- p is the probability of winning;
- q is the probability of losing, which is 1 − p.
These are the guys who created the original theory of card counting in blackjack, way before the MIT team. Some important points off the above linked research paper, keep in mind everything's proved numerically
1) Kelly's Criterion for optimal bet sizing
2) Probability estimate for reaching specific future equity levels with respect to n trials(bets)
3) Estimate of trials needed to reach specific future equity levels
4) Actual examples applied to black jack card counting, sports betting, and of course financial trading
This was the result of a 3 month sports betting strategy, applying the Kelly Ratio for each bet size. They placed 5-15 bets per day to allow for the Law of Large Numbers to kick in sooner than later. With an initial bankroll of $50k, we can see that the actual profits beat the expected a bit and ended close to 100% for the period.
1) Kelly's Criterion for optimal bet sizing
2) Probability estimate for reaching specific future equity levels with respect to n trials(bets)
3) Estimate of trials needed to reach specific future equity levels
4) Actual examples applied to black jack card counting, sports betting, and of course financial trading
This was the result of a 3 month sports betting strategy, applying the Kelly Ratio for each bet size. They placed 5-15 bets per day to allow for the Law of Large Numbers to kick in sooner than later. With an initial bankroll of $50k, we can see that the actual profits beat the expected a bit and ended close to 100% for the period.
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