This paper develops a model of optimal pricing under information uncertainty for fixed‐odds betting markets. The model suggests that bookmakers require a premium for quoting the odds several days before an event. This premium reflects the uncertainty of public information that can be exploited by expert bettors. The model predicts that when bookmakers set optimal prices, expected returns to bettors increase as a monotonic function of winning probabilities. In this manner, an information‐based explanation is given for the celebrated favourite‐longshot bias in fixed‐odds. Using an extensive data‐set of football odds from two major European bookmakers, we estimate the probability of informed betting.
The purpose of this paper is to demonstrate in a simple framework how decision tree analysis (DTA) and real options approach (ROA) yield the same results when markets are complete. The common scepticism regarding DTA has its roots in the incorrect assumption that one can apply the same discount rate to the project cash flows and the value of the investment opportunity when the decision maker has the option to defer investment. Copyright (C) 2011 John Wiley & Sons, Ltd.
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Abstract.This paper uses a new variable based on estimates of insider trading to forecast the outcome of horse races. We base our analysis on Schnytzer, Lamers and Makropoulou (2008) who showed that inside trading in the 1997-1998 Australian racetrack betting market represents somewhere between 20 and 30 percent of all trading in this market. They show that the presence of insiders leads opening prices to deviate from true winning probabilities. Under these circumstances, forecasting of race outcomes should take into account an estimate of the extent of insider trading per horse. We show that the added value of this new variable for profitable betting is sufficient to reduce the losses when only prices are taken into account. Since the only variables taken into account in either Schnytzer, Lamers and Makropoulou (2008) or this paper are price data, this is tantamount to a demonstration that the market is, in practice, weak-form efficient.
This article considers the implications of volatility estimation risk in real options theory. We construct confidence intervals for critical project values and options prices. An empirical example in lease investment evaluation for an offshore petroleum tract shows that confidence intervals can be substantial when a limited amount of data are used to estimate volatility
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