Now we will show you the optimal betting % you should use, known as Kelly Criterion.
John Kelly was a scientist who worked at Bell Labs. He discovered the optimal betting % one could use when playing in a statistically favorable game -
f* = [P*Rw - (1-P)*R1]/(Rw*R1) or f = P/R1 - (1-P)/Rw
where:
- f* is the fraction of the current bankroll to wager, i.e. how much to bet;
- p is the probability of winning;
- q is the probability of losing, which is 1 − p;
- Rw is the net winning %
- Rl is the net losing %
In our previous example where a gambler has a 60% chance of winning (p = 0.60, q = 0.40), and Rw=1 and Rl=1, the gambler should bet 20% of his bankroll at each opportunity (f* = 0.20).
If in a game the gambler has zero edge, i.e. p = q, and Rw = Rl, then the Kelly criterion recommends the gambler bets nothing.
With a good understanding of the Kelly Risk Control Strategy, you could apply it to your investment's decision and achieve amazing results.
For example, if you have found a winning strategy in the stock market with 80% of chance of net winning rate of 3%, and 20% of chance of net losing 5%, even with such a high odds of winning, you definitely shouldn't all in, in fact, based on Kelly formula, your optimal betting % each time should be only 9.33%!
In our next blog post, we will derive the investor's expected optimal compound growth rate, based on the Kelly formula.