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Unformatted text preview: Markov Chain, part 2 December 12, 2010 1 The gambler’s ruin problem Consider the following problem. Problem. Suppose that a gambler starts playing a game with an initial $B bank roll. The game proceeds in turns, where at the end of each turn the gambler either wins $1 with probability p , or loses $1 with probability q = 1 − p . The player continues until he or she either makes it to $N, or goes bankrupt with $0. Determine the probability that the player eventually reaches the $N. We can represent this by a Markov chain having N +1 states representing the amount of money that the player has: either $0, $1, ..., or $N. The transition probabilities are given as follows: P , = 1; P N,N = 1; and P i,i +1 = p and P i,i 1 = q for i = 1 , 2 , ..., N − 1. The corresponding transition matrix is P = 1 q 0 0 0 · · · 0 0 0 0 q 0 0 · · · 0 0 p q · · · 0 0 0 0 p q · · · 0 0 . . . . . . . . . . . . . . . . . . . . . . . . 0 0 0 0 0 · · · q 0 0 0 0 0 · · · 0 0 0 0 0 0 0 · · · p 1 ....
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This note was uploaded on 10/23/2011 for the course MATH 3225 taught by Professor Staff during the Spring '08 term at Georgia Tech.
 Spring '08
 Staff
 Statistics, Probability

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