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This paper investigates fundamental investment strategies to detect and exploit the public's systematic errors in horse race wager markets. A handicapping model is developed and applied to win-betting in the pari-mutuel system. A multinomial logit model of the horse racing process is posited and estimated on a data base of 200 races. A recently developed procedure for exploiting the information content of rank ordered choice sets is employed to obtain more efficient parameter estimates. The variables in this discrete choice probability model include horse and jockey characteristics, plus several race-specific features. Hold-out sampling procedures are employed to evaluate wagering strategies. A wagering strategy that involves unobtrusive bets, with a side constraint eliminating long-shot betting, appears to offer the promise of positive expected returns, even in the presence of the typically large track take encountered at Thoroughbred racing events.multinomial logit model, horse race wagering, stochastic utility model, ranked choice set data, discrete choice modeling

Advances in digital technology are transforming the marketplace-requiring rapid innovation by colleges and universities (AACSB, 2016). Business schools have embraced technology platforms to advance and customize learning, including online, modular, collaborative, and just-in-time learning experiences (

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