Abstract
A favorable game is one in which, loosely speaking, there are opportunities for favorable bets. We consider only games where there is a "double or nothing" return of the stake, the win probability $p$ being drawn independently each day from a distribution $F(p)$, and told to the player before he makes his bet. We are interested, not in maximizing the expected fortune over a number of plays, but in minimizing the probability of eventual ruin. In order that the gambler cannot stand pat, we use two devices. In Model I, he must pay a fee of $1 after each play. In Model II, he must bet a minimum of $1. His bet may never exceed his current fortune, $x$. Let $b$ denote an allowable betting strategy. We define the ruin function by $q(x) = \inf_bP$ (ruin $\mid b$, starting fortune $x$). In both models, if ever $x < 1$, ruin is inevitable. In Section 3, we introduce (following Ferguson, [3]) the idea of a loss function, $q_o(x)$, satisfying certain conditions. A "natural" choice for loss function is $q_0^\ast(x) = 1$ for $x < 1, = 0$ otherwise. We define the minimal expected loss after $n$ games by $q_n(x) = \inf_bEq_0(X_n)$ where $X_n$ is the fortune after the $n$th game. In Lemmas 3.1-3.5, we construct a suitable Borel-measurable betting function to show that $q_n(x)$ satisfies the dynamic programming relationship; if $x \rightarrow X_1(b_1)$ after bet $b_1$, then $q_n(x) = \inf_{b_1} Eq_{n-1} (X_1(b_1))$. The results of Section 3 do not depend on the assumption that the game is favorable, but from now on this assumption is required. Using the natural loss function $q_0^\ast(x)$, we show in Lemma 4.1 that $q_n^\ast(x) \rightarrow q(x)$ as $n \rightarrow \infty$, uniformly in $x$ (in passing, Theorem 5.1 shows that for any loss function, $q_n(x) \rightarrow q(x)$ without uniformity) and we employ this result in Section 6 to show that $q(x)$ is continuous, for Model I only. For both models, $q(x)$ is already known [1] to be lower semi-continuous. These results are sufficient to establish [3] that a particular stationary Markov betting function, $b^\ast(x, p)$, is optimal (although not necessarily unique). For large fortunes $x$, asymptotic forms for the ruin function $q(x)$, and as a consequence for $b^\ast(x, p)$, are already known [1], [3] under a slight restriction on $F(p)$, namely that it have no mass in a neighborhood of 1. On removing the restriction, some weaker results are obtained, and summarized in Section 8.
Citation
Alan J. Truelove. "Betting Systems in Favorable Games." Ann. Math. Statist. 41 (2) 551 - 566, April, 1970. https://doi.org/10.1214/aoms/1177697095
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