In 1979 [Studies in Intelligence, Vol. 23, No. 1 (Spring 1979)], a study of expert handicappers demonstrated an interesting interaction between information and confidence. There were two key findings. First, as soon as an experienced handicapper has the minimum information (seven plus or minus two variables) necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his selections. Second, additional information does, however, lead the handicapper to become more confident in his judgments, to the point of overconfidence. It appears that handicappers have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information.
As ever, if the handicapper cannot find variables that account for sufficient variance in outcomes over and above that provided by market prices then he will not have an edge and will lose his bankroll.
Showing posts with label Gambler's Ruin. Show all posts
Showing posts with label Gambler's Ruin. Show all posts
Sunday, November 06, 2011
Information Calibration And Confidence
Labels:
Betting,
Expert,
Gambler's Ruin,
Handicapper,
Psychology
Thursday, February 25, 2010
Even-Equivalent Probability of Ruin
Epstein (2009) provides a detailed, mathematical analysis of the risk of ruin within the broader context of the basic theorems of gambling. Without loss of generality, it is worth providing a layman’s interpretation of how the probability of ruin impacts the choices made by the average handicapper.
In the classic treatment of ruin, there is a working assumption of unit bets at even-money in order to make the calculation of the risk of ruin more tractable. To avail ourselves of this analytical solution, we need to transform our real-world bets into their even-money equivalents, see Krigman (1999).

For example, if you are in the fortunate position outlined above with a 42% strike rate at an average price of 2.50 then your advantage is the equivalent of having a win probability of 52.02% at 2.00 with both the same expected value and standard deviation (0.25, 6.169) as the original bet and with a probability of ruin equal to 24.07%. Obviously, it is also possible to estimate stake size given a specific price and preferred risk of ruin.
In the classic treatment of ruin, there is a working assumption of unit bets at even-money in order to make the calculation of the risk of ruin more tractable. To avail ourselves of this analytical solution, we need to transform our real-world bets into their even-money equivalents, see Krigman (1999).

For example, if you are in the fortunate position outlined above with a 42% strike rate at an average price of 2.50 then your advantage is the equivalent of having a win probability of 52.02% at 2.00 with both the same expected value and standard deviation (0.25, 6.169) as the original bet and with a probability of ruin equal to 24.07%. Obviously, it is also possible to estimate stake size given a specific price and preferred risk of ruin.
Labels:
Epstein,
Gambler's Ruin,
Krigman
Thursday, January 21, 2010
Gamblers Ruin at Casino Incroyable
A nice mixture of mathematics and humor - Gamblers Ruin at Casino Incroyable with passing reference to "Bold Play", "Minimum Gain", and "Gamblers Ruin".
Labels:
Bold Play,
Gambler's Ruin
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