Risk free betting and profiting from statistics formulas

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Thus, using too much margin is not a good investment strategy when the cost of capital is high, even when the opportunity appears promising. Heuristic proofs of the Kelly criterion are straightforward. This gives:. For a rigorous and general proof, see Kelly's original paper [1] or some of the other references listed below. Some corrections have been published. The resulting wealth will be:. After the same series of wins and losses as the Kelly bettor, they will have:. This illustrates that Kelly has both a deterministic and a stochastic component.

If one knows K and N and wishes to pick a constant fraction of wealth to bet each time otherwise one could cheat and, for example, bet zero after the K th win knowing that the rest of the bets will lose , one will end up with the most money if one bets:. The heuristic proof for the general case proceeds as follows. Edward O. Thorp provided a more detailed discussion of this formula for the general case. In practice, this is a matter of playing the same game over and over, where the probability of winning and the payoff odds are always the same.

In a article, Daniel Bernoulli suggested that, when one has a choice of bets or investments, one should choose that with the highest geometric mean of outcomes. This is mathematically equivalent to the Kelly criterion, although the motivation is entirely different Bernoulli wanted to resolve the St. Petersburg paradox. An English-language translation of the Bernoulli article was not published until , [14] but the work was well-known among mathematicians and economists.

Kelly's criterion may be generalized [15] on gambling on many mutually exclusive outcomes, such as in horse races. Suppose there are several mutually exclusive outcomes. The algorithm for the optimal set of outcomes consists of four steps. One may prove [15] that. The binary growth exponent is. In this case it must be that. In mathematical finance, a portfolio is called growth optimal if security weights maximize the expected geometric growth rate which is equivalent to maximizing log wealth.

Computations of growth optimal portfolios can suffer tremendous garbage in, garbage out problems. Ex-post performance of a supposed growth optimal portfolio may differ fantastically with the ex-ante prediction if portfolio weights are largely driven by estimation error.

Dealing with parameter uncertainty and estimation error is a large topic in portfolio theory. The second-order Taylor polynomial can be used as a good approximation of the main criterion. Primarily, it is useful for stock investment, where the fraction devoted to investment is based on simple characteristics that can be easily estimated from existing historical data — expected value and variance.

This approximation leads to results that are robust and offer similar results as the original criterion. Considering a single asset stock, index fund, etc. Taking expectations of the logarithm:. Thorp [13] arrived at the same result but through a different derivation. Confusing this is a common mistake made by websites and articles talking about the Kelly Criterion. The above formula can be used to calculate the average result of making that bet a large number of times. If it is greater than 0, you should make the bet.

This situation, at its most basic level, deals with information in a game. However, this is not the case, so we utilize the information imbalance to profit from this game. Generally, whenever you feel that the odds do not accurately represent the true probabilities involved, you should make a bet that takes advantage of this imbalance by betting on the undervalued party. Now that we have the gist of how we can reliably profit from betting, we now need a formal way to determine our bet sizes.

Responsible bet sizing is essential, as going too high on a risky bet could prematurely bankrupt you and going too low on a safer bet could result in winnings too small to justify taking any risk at all. One such strategy for this is called the Kelly Criterion , which is a very simple formula to determine the fraction of your total money to use on each bet.

However, while this is effectively a mathematically-correct way to bet, most rational people will use a fraction of this amount in practice, as the full Kelly can be quite risky. In real life, we do not have an infinite amount of money to gamble, so we risk ruin.

If your personal probabilities are off, which is likely to happen at some point, you can lose a lot of money very quickly. Quarter-Kelly, or lower, are common modifications that can make the technique more viable. Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday. Make learning your daily ritual. Take a look. Get started. Open in app. Sign in. Editors' Picks Features Explore Contribute. Betting Optimally. Use the Kelly criterion to size your bets when gambling.

Expected value Simply put, the expected value of a random variable is the average value it will hold over a large number of repetitions of the experiment it is involved in. Kelly criterion — a mathematical strategy for betting Now that we have the gist of how we can reliably profit from betting, we now need a formal way to determine our bet sizes.

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The various types are represent different formats to present probabilities, which are also used by bookmakers, and one type can be converted into another. Once the implied probability for an outcome is known, decisions can be made regarding whether or not to place a bet or wager. Although odds require seemingly complicated calculations, the concept is easier to understand once you fully grasp the three types of odds and how to convert the numbers into implied probabilities.

There are tools available to make conversions between the three types of odds. Many online betting websites offer an option to display the odds in the preferred format. The table below can help convert odds with pen and paper, for those interested in doing the calculations by hand.

Converting odds to their implied probabilities is perhaps the most interesting part. The general rule for the conversion of any type of odds into an implied probability can be expressed as a formula:. As shown, the formula divides the stake amount wagered by the total payout to get the implied probability of an outcome.

Plug the numbers into the formula, which is a simple matter of dividing 8 by 13 in this example, and the implied probability equals The higher the number, the greater the probability of the outcome. Using an example of decimal odds, a candidate has 2. If so, the implied probability is Therefore, the implied probability equals Moreover, the odds displayed by different bookmakers can vary significantly, meaning that the odds displayed by a bookmaker are not always correct.

The key is to consider a betting opportunity valuable when the probability assessed for an outcome is higher than the implied probability estimated by the bookmaker. The odds on display never reflect the true probability or chance of an event occurring or not occurring. There is always a profit margin added by the bookmaker in these odds, which means that the payout to the successful punter is always less than what they should have received if the odds had reflected the true chances.

The bookmaker needs to estimate the true probability or chance of an outcome correctly in order to set the odds on display in such a way that it profits the bookmaker regardless of an event outcome. If you notice, the total of these probabilities is This is because the odds on display are not fair odds.

The bookie has an edge built into the odds. According to a study published in the Journal of Gambling Studies , the more hands a player wins, the less money they are likely to collect, especially with respect to novice players. Behavioral economics comes into play here. A player continues playing the lottery , either in hopes of a big gain that would eventually offset the losses or the winning streak compels the player to keep playing.

In both cases, it is not rational or statistical reasoning but the emotional high of a win that motivates them to play further. Consider a casino. The house wants you to stay and continue playing. Naturally, the games offered by the casino have a built-in house edge, although the house advantage varies with the game.

Moreover, novices find it particularly difficult to do cognitive accounting and people often misjudge the variance of payouts when they have a streak of wins, ignoring the fact that frequent modest gains are eventually erased by losses, which are often less frequent and larger in size. A betting opportunity should be considered valuable if the probability assessed for an outcome is higher than the implied probability estimated by the bookmaker.

Furthermore, the odds on display never reflect the true probability of an event occurring or not occurring.