Pari-mutuel Market Research Articles

The Survival of the Unfittest

We explore the use of parimutuel markets in a peer- to-peer setting to generate a wide diversity of content offerings while responding adaptively to customer demand. Files are served and paid for through a parimutuel market similar to that used for betting in horse races and in lotteries. Our simulations are based on rational agents, which all act according to a set of simple rules. The results show that a favorite-long-shot bias occurs, where agents tend to bet on long-shots rather than favorites when following simple expected utility maximization. Furthermore, we have confirmed that the long-tail does sustain even when the agents only have a limited view of all files to pick from. If the limited view consists of random subsets of all files, the long tail is enhanced. If the limited view consists of the top most popular items, the long tail slightly decreases. We have also explored the effect of bounded rationality. Our results show that the system is robust in presence of a large fraction of providers that have bounded rationality. If the providers with bounded rationality pick random items, the long tail is enhanced. Conversely, if the providers with bounded rationality only pick their favorite, the long tail slightly decreases.

Data, knowledge, and common sense reasoning

We explore the use of pari-mutuel markets in a peer-to-peer setting to generate a wide diversity of content offerings while responding adaptively to customer demand. Files are served and paid for through a parimutuel market similar to that used for betting in horse races and in lotteries. Our simulations are based on rational agents, which all act according to a set of simple rules. The results show that a favorite-longshot bias occurs, where agents tend to bet on longshots rather than favorites when following simple expected utility maximization. Furthermore, we have con- firmed that the long-tail does sustain even when the agents only have a limited view of all files to pick from. If the limited view consists of random subsets of all files, the long tail is enhanced. If the limited view consists of the top most popular items, the long tail slightly decreases. We have also explored the effect of bounded rationality. Our results show that the system is robust in presence of a large fraction of providers that have bounded rationality. If the providers with bounded rationality pick random items, the long tail is enhanced. Conversely, if the providers with bounded rationality only pick their favorite, the long tail slightly decreases.

Prediction Market Performance and Market Liquidity: A Comparison of Automated Market Makers

The use of prediction markets (PMs) for forecasting is emerging in many fields because of its excellent forecasting accuracy. However, PM accuracy depends on its market design, including the choice of market mechanism. Standard financial market mechanisms are not well suited for small, usually illiquid PMs. To avoid liquidity problems, automated market makers (AMMs) always offer buy and sell prices. However, there is limited research that measures the relative performance of AMMs. This paper examines the properties of four documented and applied AMMs and compares their performance in a large-scale simulation study. The results show that logarithmic scoring rules and the dynamic pari-mutuel market attain the highest forecasting accuracy, good robustness against parameter misspecification, the ability to incorporate new information into prices, and the lowest losses for market operators. However, they are less robust in case of noisy trading, which makes them less appropriate in environments with high uncertainty about true prices for shares.

Efficiency in Pari-Mutuel Betting Markets across Wagering Pools in the Simulcast Era

1. IntroductionPari-mutuel wagering has been much studied in economics and finance because it functions as a controlled repeated experiment of an asset market (see Sauer 1998 for an overview). Through pari-mutuel betting, the public collectively establishes a price on each betting interest, and these prices have been found to be fairly accurate in representing the true value of the bet. The track acts as a market maker, extracting a fixed percentage (14-20%) from betting pools and redistributing the rest to the holders of the winning tickets. Because the market is repeated numerous times daily at tracks across the world, an abundance of data exists on betting markets. Furthermore, with the proliferation of simulcasting races, participation in the pari-mutuel market is no longer restricted to just those attending the races.In a speculative market, efficiency dictates that the expected return on an asset should equal the return on the entire market. Betting-market efficiency requires that no betting strategy generates above-market returns after accounting for costs (see Vaughan Williams 1999 for an extensive review of the literature). Thaler and Ziemba (1988) define a weak and strong condition for betting-market efficiency. Weak-form efficiency requires that no bets have positive expected returns. Strong-form efficiency requires all bets to have the same expected return equal to one minus the track take. Therefore, under strong-form efficiency, the probability of a horse winning a race would be equal to the percentage of money bet on that horse.This article is an empirical analysis of straight wagers, which are bets on a horse to win, place (finish in the top two), or show (finish in the top three). Numerous empirical studies have found the existence of a bias on win wagers such that favorites were underbet relative to long shots, resulting in a higher expected return for low-odds horses (Ali 1977; Asch, Malkiel, and Quandt 1982). However, other studies have found a reverse favorite-long shot bias (Busche and Hall 1988; Swindler and Shaw 1995). Explanations of the bias have included risk preference (Ali 1977; Golec and Tamarkin 1998), information disparities (Hurley and McDonough 1995, 1996; Terrell and Farmer 1996; Gandar, Zuber, and Johnson 2001), transaction costs (Hurley and McDonough 1995, 1996; Vaughan Williams and Paton 1998a, b), and market size (Busche and Walls 2000). Previous studies on place and show betting have found even more pronounced biases, and these findings have led to the formulation of profitable betting strategies, the most prominent being Ziemba and Hausch's Beat the Racetrack (Ziemba and Hausch 1984; Asch, Malkiel, and Quandt 1984, 1986; Asch and Quandt 1986; Hausch, Ziemba, and Rubinstein 1981; Hausch and Ziemba 1985). There have been few articles on betting simulations and efficiency, the most notable being Goodwin (1996), who uses forecasts of conditional probabilities to earn above-market returns.The proliferation of simulcast wagering has created an environment where relatively few betting patrons attend the races anymore, and those that do are more likely to be found in front of a television carrel watching races from around the country, rather than in the grandstand. Previously, tracks would simulcast only major races a few times a year and have their own separate betting pools for these races. A betting pool at a given track for a given race would be comprised of money from people at the track and in some instances, from off-track betting sites or phone accounts, both within the track's home state. Today, simulcast wagering allows bettors to play a multitude of races at many tracks across the country, from their home track, casino, off-track betting hub, by phone, or online, and their bets are commingled into the same pool as those made at the host track. This development has resulted in an explosion in the dollar volume wagered on horse racing in the last decade. …

The Tech Buzz Game [stock market prediction

Prediction markets, also known as information or decision markets, are designed to forecast future events or trends. Internet-based prediction markets can easily aggregate the insights of an unlimited number of potentially knowledgeable people asynchronously. The Tech Buzz Game - a joint venture between Yahoo! Research Labs and O'Reilly Media - is a fantasy prediction market launched in March 2005 at the O'Reilly Emerging Technology (ETech) Conference. The game consists of multiple sub-markets that pit a handful of rival technologies, each represented by a stock, against one another. The game's object is to anticipate future search buzz and buy and sell stocks accordingly. Thus, a player who believes BitTorrent stock is undervalued might buy shares, while a player who thinks BitTorrent is overpriced might sell the stock or instead purchase shares in a competing peer-to-peer technology. The Tech Buzz Game serves two key research-oriented goals. One is to evaluate the power of prediction markets to forecast high-tech trends. The other goal of the Tech Buzz Game is to field test the dynamic pari-mutuel market, a Yahoo! Research Labs trading mechanism designed to price and allocate shares.

A Parimutuel Market Microstructure for Contingent Claims Trading

A parimutuel market microstructure for contingent claims trading is proposed and analyzed. A parimutuel microstructure is a call auction where relative equilibrium prices of contingent claims are endogenously determined using a specific mechanism. We propose a market microstructure incorporating parimutuel principles which provides for notional derivatives transactions, limit orders, and bundling of contingent claims across states. This microstructure will be used by Longitude Inc.'s clients to transact derivatives on economic statistics, weather, insurance losses and other types of risks. JPMorgan Chase and Deutsche Bank are some of the financial institutions that will be holding parimutuel auctions in early 2002.

An Examination of Efficiency in British Racetrack Betting: Errata and Corrections

Previous articleNext article No AccessConfirmations and ContradictionsAn Examination of Efficiency in British Racetrack Betting: Errata and CorrectionsPaul Gabriel, and James R. MarsdenPaul Gabriel Search for more articles by this author , and James R. Marsden Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Journal of Political Economy Volume 99, Number 3Jun., 1991 Article DOIhttps://doi.org/10.1086/261772 Views: 2Total views on this site Citations: 21Citations are reported from Crossref Copyright 1991 The University of ChicagoPDF download Crossref reports the following articles citing this article:Chi Zhang, Jacco Thijssen On Sticky Bookmaking as a Learning Device in Horse-Racing Betting Markets, Journal of Economic Dynamics and Control 85 (Sep 2022): 104525.https://doi.org/10.1016/j.jedc.2022.104525Chung-Ching Tai, Hung-Wen Lin, Bin-Tzong Chie, Chen-Yuan Tung Predicting the failures of prediction markets: A procedure of decision making using classification models, International Journal of Forecasting 35, no.11 (Jan 2019): 297–312.https://doi.org/10.1016/j.ijforecast.2018.04.003Jianbo Li, Minggao Gu, Riquan Zhang, Heng Lian Variable selection for general transformation models with ranking data, Statistics 48, no.11 (Aug 2012): 81–100.https://doi.org/10.1080/02331888.2012.708034Jianbo Li, Minggao Gu, Tao Hu General partially linear varying-coefficient transformation models for ranking data, Journal of Applied Statistics 39, no.77 (Jul 2012): 1475–1488.https://doi.org/10.1080/02664763.2012.658357J.E.V. Johnson, D. Peel, J. Peirson Systematic and varying biases in parallel state contingent gambling markets, Economics Letters 109, no.22 (Nov 2010): 82–84.https://doi.org/10.1016/j.econlet.2010.08.015Jaiho Chung, Joon Ho Hwang An Empirical Examination of the Parimutuel Sports Lottery Market versus the Bookmaker Market, Southern Economic Journal 76, no.44 (Apr 2010): 884–905.https://doi.org/10.4284/sej.2010.76.4.884M. SUNG, J. E. V. JOHNSON Revealing Weak-Form Inefficiency in a Market for State Contingent Claims: The Importance of Market Ecology, Modelling Procedures and Investment Strategies, Economica 77, no.305305 (Jan 2010): 128–147.https://doi.org/10.1111/j.1468-0335.2008.00716.xErik Snowberg, Justin Wolfers Examining Explanations of a Market Anomaly: Preferences or Perceptions?, (Jan 2008): 103–136.https://doi.org/10.1016/B978-044450744-0.50010-XRussell S. Sobel, Matt E. Ryan Unifying the Favorite-Longshot Bias with Other Market Anomalies, (Jan 2008): 137–160.https://doi.org/10.1016/B978-044450744-0.50011-1M. Sung, J.E.V. Johnson Semi-Strong Form Information Efficiency in Horse Race Betting Markets, (Jan 2008): 275–306.https://doi.org/10.1016/B978-044450744-0.50017-2Alexander K. Koch, Hui-Fai Shing Bookmaker and Pari-Mutuel Betting: Is a (Reverse) Favourite-Longshot Bias Built-In?, SSRN Electronic Journal (Jan 2007).https://doi.org/10.2139/ssrn.964438Leighton Vaughan Williams Semi-strong and strong form information efficiency in betting markets, (Sep 2005): 123–156.https://doi.org/10.1017/CBO9780511493614.004Ming-Chien Sung, Johnnie E. V. Johnson, Alistair C. Bruce Searching for semi-strong form inefficiency in the UK racetrack betting market, (Sep 2005): 179–192.https://doi.org/10.1017/CBO9780511493614.007Ivan. A. Paya, David. A. Peel, David. Law, John. Peirson Testing for market efficiency in gambling markets: some observations and new statistical tests based on a bootstrap method, (Sep 2005): 346–365.https://doi.org/10.1017/CBO9780511493614.018Alistair C. Bruce, Johnnie E.V. Johnson Market ecology and decision behaviour in state-contingent claims markets, Journal of Economic Behavior & Organization 56, no.22 (Feb 2005): 199–217.https://doi.org/10.1016/j.jebo.2003.09.009Jeffrey Lange, Nicholas Economides A Parimutuel Market Microstructure for Contingent Claims, European Financial Management 11, no.11 (Jan 2005): 25–49.https://doi.org/10.1111/j.1354-7798.2005.00274.xAlistair C. Bruce, Johnnie E. V. Johnson Efficiency characteristics of a market for state contingent claims, Applied Economics 33, no.1313 (Oct 2001): 1751–1754.https://doi.org/10.1080/00036840110052785Jeffrey Lange, Nicholas Economides A Parimutuel Market Microstructure for Contingent Claims Trading, SSRN Electronic Journal (Jan 2001).https://doi.org/10.2139/ssrn.294306Alistair C. Bruce, Johnnie E.V. Johnson Market efficiency analysis requires a sensitivity to market characteristics: some observations on a recent study of betting market efficiency, Applied Economics Letters 7, no.33 (Oct 2010): 199–202.https://doi.org/10.1080/135048500351799Leighton Vaughan Williams, David Paton Does information efficiency require a perception of information inefficiency?, Applied Economics Letters 4, no.1010 (Oct 1997): 615–617.https://doi.org/10.1080/758533285Paul E. Gabriel, James R. Marsden, Timothy J. Stanton Testing market efficiency with information on individual investor performance, International Review of Economics & Finance 2, no.22 (Jan 1993): 149–162.https://doi.org/10.1016/1059-0560(93)90020-Q