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  2. Gambler's ruin - Wikipedia

    en.wikipedia.org/wiki/Gambler's_ruin

    In statistics, gambler's ruin is the fact that a gambler playing a game with negative expected value will eventually go bankrupt, regardless of their betting system.. The concept was initially stated: A persistent gambler who raises his bet to a fixed fraction of the gambler's bankroll after a win, but does not reduce it after a loss, will eventually and inevitably go broke, even if each bet ...

  3. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    If the Markov chain is time-homogeneous, then the transition matrix P is the same after each step, so the k-step transition probability can be computed as the k-th power of the transition matrix, P k. If the Markov chain is irreducible and aperiodic, then there is a unique stationary distribution π. [41]

  4. Risk of ruin - Wikipedia

    en.wikipedia.org/wiki/Risk_of_ruin

    Risk of ruin is a concept in gambling, insurance, and finance relating to the likelihood of losing all one's investment capital or extinguishing one's bankroll below the minimum for further play. [1] For instance, if someone bets all their money on a simple coin toss, the risk of ruin is 50%.

  5. Optional stopping theorem - Wikipedia

    en.wikipedia.org/wiki/Optional_stopping_theorem

    Then the gambler's fortune over time is a martingale, and the time τ at which he decides to quit (or goes broke and is forced to quit) is a stopping time. So the theorem says that E[X τ] = E[X 0]. In other words, the gambler leaves with the same amount of money on average as when he started. (The same result holds if the gambler, instead of ...

  6. Stochastic process - Wikipedia

    en.wikipedia.org/wiki/Stochastic_process

    In his first paper on Markov chains, published in 1906, Markov showed that under certain conditions the average outcomes of the Markov chain would converge to a fixed vector of values, so proving a weak law of large numbers without the independence assumption, [296] [297] [298] which had been commonly regarded as a requirement for such ...

  7. Examples of Markov chains - Wikipedia

    en.wikipedia.org/wiki/Examples_of_Markov_chains

    A game of snakes and ladders or any other game whose moves are determined entirely by dice is a Markov chain, indeed, an absorbing Markov chain. This is in contrast to card games such as blackjack, where the cards represent a 'memory' of the past moves. To see the difference, consider the probability for a certain event in the game.

  8. List of probability topics - Wikipedia

    en.wikipedia.org/wiki/List_of_probability_topics

    Gambler's fallacy; Inverse gambler's fallacy; Parrondo's paradox; Pascal's wager; Gambler's ruin; Poker probability. Poker probability (Omaha) Poker probability (Texas hold 'em) Pot odds; Roulette. Martingale (betting system) The man who broke the bank at Monte Carlo; Lottery. Lottery machine; Pachinko; Coherence (philosophical gambling ...

  9. Gambling and information theory - Wikipedia

    en.wikipedia.org/wiki/Gambling_and_information...

    When these constraints apply (as they invariably do in real life), another important gambling concept comes into play: in a game with negative expected value, the gambler (or unscrupulous investor) must face a certain probability of ultimate ruin, which is known as the gambler's ruin scenario. Note that even food, clothing, and shelter can be ...