THE EFFECT OF CONTRACT STRUCTURE ON PREDICTION MARKET PRICE BIASES

2012 ◽  
Vol 3 (3) ◽  
pp. 1-12
Author(s):  
Richard Borghesi
Keyword(s):  
Significant Role ◽  
Market Price ◽  
Prediction Markets ◽  
Prediction Market ◽  
Price Efficiency ◽  
Combine Score ◽  
Structural Differences ◽  
Unbiased Estimates ◽  
Contract Structure

Prediction markets add value when they produce unbiased forecasts.  However, several prior studies find persistent biases when examining prediction market sides contracts.  Sides contracts represent bets on whether the score differential between two teams in a contest will be greater or less than a stated value.  We propose that inferences generated from examining Tradesports’ sides contracts may be problematic because they are framed exclusively with respect to favorites.  If a favorite-longshot (or reverse favorite-longshot) bias causes these deviations from rationality, it may be that non-sports-related (e.g., internal corporate) prediction markets assets do not suffer from the same shortcomings.  To evaluate the generalizability of prior findings, we contrast the price efficiency of Tradesports’ sides and totals contracts.  In totals wagers, traders take a position on whether the combine score of both teams in a game will be above or below a stated value.  We find that the fundamental structural differences between totals contracts and sides contracts partly determine differences in price efficiencies.  Relative to those in the sides market, some price biases in the totals market are significantly smaller in magnitude, and others are absent altogether.  Results indicate that contract structure plays a significant role in the ability of prediction markets to produce unbiased estimates.

scholarly journals Prediction Markets for Crowdsourcing

2018 ◽  
Author(s):  
Christian Horn ◽  
Marcel Bogers ◽  
Alexander Brem*
Keyword(s):  
Stock Market ◽  
Open Innovation ◽  
Innovation Process ◽  
Business Practice ◽  
Prediction Markets ◽  
Knowledge Sources ◽  
Prediction Market ◽  
Online Platform ◽  
External Knowledge ◽  
Opening Up

Crowdsourcing is an increasingly important phenomenon that is fundamentally changing how companies create and capture value. There are still important questions with respect to how crowdsourcing works and can be applied in practice, especially in business practice. In this chapter, we focus on prediction markets as a mechanism and tool to tap into a crowd in the early stages of an innovation process. The act of opening up to external knowledge sources is also in line with the growing interest in open innovation. One example of a prediction market, a virtual stock market, is applied to open innovation through an online platform. We show that use of mechanisms of internal crowdsourcing with prediction markets can outperform use of external crowds.

Optimizing the liquidity parameter of logarithmic market scoring rules prediction markets

2018 ◽  
Vol 13 (3) ◽  
pp. 736-754
Author(s):  
Suparerk Lekwijit ◽  
Daricha Sutivong
Keyword(s):  
Standard Error ◽  
Market Price ◽  
Simulation Models ◽  
Scoring Rules ◽  
Prediction Markets ◽  
Market Mechanisms ◽  
Content Type ◽  
Market Makers ◽  
True Value ◽  
Price Functions

Purpose Prediction markets are techniques to aggregate dispersed public opinions via market mechanisms to predict uncertain future events’ outcome. Many experiments have shown that prediction markets outperform other traditional forecasting methods in terms of accuracy. Logarithmic market scoring rules (LMSR) is one of the most simple and widely used market mechanisms; however, market makers have to confront crucial design decisions including the setting of the parameter “b” or the “liquidity parameter” in the price functions. As the liquidity parameter has significant effects on the market performance, this paper aims to provide a comprehensive basis for the setting of the parameter. Design/methodology/approach The analyses include the effects of the liquidity parameter on the forecast standard error and the amount of time for the market price to converge to the true value. These experiments use artificial prediction markets, the proposed simulation models that mimic real prediction markets. Findings The simulation results indicate that prediction market’s forecast standard error decreases as the value of the liquidity parameter increases. Moreover, for any given number of traders in the market, there exists an optimal liquidity parameter value that yields appropriate price adaptability and leads to the fastest price convergence. Originality/value Understanding these tradeoffs, the market makers can effectively determine the liquidity parameter value under various objectives on the standard error, the time to convergence and cost.

AN EXAMINATION OF PREDICTION MARKET EFFICIENCY: NBA CONTRACTS ON TRADESPORTS

2012 ◽  
Vol 3 (2) ◽  
pp. 65-77
Author(s):  
Richard Borghesi
Keyword(s):  
Market Efficiency ◽  
Theoretical Work ◽  
Relative Price ◽  
Event Data ◽  
Prediction Market ◽  
Price Efficiency ◽  
The Absolute ◽  
Fundamental Values ◽  
Vaughan Williams

In this paper I examine the absolute and relative price efficiency of NBA options listed on Tradesports.com.  I find that contracts within specific price bands are misvalued, but also demonstrate that this market is more efficient than is the market for NFL options.  Specifically, I show that contracts priced around $25 win (expire at $100) at a rate less than expected, while those priced around $75 win at a rate greater than expected.  The magnitudes of these deviations between prices and fundamental values are less than those in the NFL market.  Also, while prior theoretical work predicts that low-priced contracts should be overpriced, I instead find that NBA contracts priced near $2.50 win more frequently than expected.I thank Rob Dougherty and Brijesh Patel for assistance with the NBA event data, and Leighton Vaughan Williams for meaningful suggestions throughout.  Any errors are strictly my own.

A STATISTICAL MODEL OF CLAIM PRICES IN PREDICTION MARKETS

2012 ◽  
Vol 4 (3) ◽  
pp. 85-93
Author(s):  
Russ Ray
Keyword(s):  
Statistical Model ◽  
Financial Markets ◽  
Poisson Distribution ◽  
Prediction Markets ◽  
Inside Information ◽  
Prediction Market ◽  
The World ◽  
Global Agreement ◽  
High Degree

This paper finds that claim prices in prediction markets, a new genre of financial markets, follow a Poisson distribution. The significance of this finding is that as soon as a claim in a prediction market is created and thereafter flushes out expert and inside information from around the world regarding that particular claim, claim prices immediately begin forming bell-shaped distributions, implying global agreement regarding the probabilities of claims being realized. This is an interesting finding, implying a surprisingly high degree of global homogeneity of inside information in predictions markets, even though such information is scattered in disconnected and secretive pockets around the world. This finding could also imply that cultural diversities do not significantly affect the interpretation of information in prediction markets. 

Evidencing the Forecasting Performance of Predication Markets: An Empirical Comparative Study

2018 ◽  
Vol 11 (2) ◽  
pp. 60-76
Author(s):  
Patrick Buckley
Keyword(s):  
Empirical Studies ◽  
Academic Research ◽  
Relevant Information ◽  
Prediction Markets ◽  
Problem Space ◽  
Prediction Market ◽  
Forecasting Performance ◽  
Planning Processes ◽  
Uncertain Outcomes ◽  
Aid Decision

Accurately forecasting uncertain outcomes to inform planning processes and aid decision making is a perennial organisational challenge, and the focus of a substantial body of research in management science, information systems and related disciplines. Academic research suggests that prediction markets may be of significant benefit to organisations in meeting this challenge. However most of the empirical studies assessing prediction market performance are laboratory based and suffer from limits to their generalizability. Recent literature has called for research which analyses the performance of prediction markets in ecologically valid settings in order to evidence their effectiveness to potential organisational users. This paper answers these calls by designing a prediction market to forecast an uncertain real world event. The study then compares the forecasting performance of the prediction market with a number of more traditional forecasting approaches regularly used by organisations. The study is contextually situated in a low information heterogeneity problem space, where relevant information is freely available. The results suggest that in this context prediction markets outperform the other forecasting methods studied.

PRIVATE PREDICTION MARKETS AND THE LAW

2012 ◽  
Vol 3 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Tom Bell
Keyword(s):  
Prediction Markets ◽  
Management Decisions ◽  
Prediction Market ◽  
The Public ◽  
Legal Risks ◽  
Federal Laws ◽  
The Law ◽  
Considerable Benefit

This paper analyses the legality of private prediction markets under U.S. law, describing both the legal risks they raise and how to manage those risks.  As the label "private" suggests, such markets offer trading not to the public but rather only to members of a particular firm.  The use of private prediction markets has grown in recent years because they can efficiently collect and quantify information that firms find useful in making management decisions.  Along with that considerable benefit, however, comes a worrisome cost:  the risk that running a private prediction market might violate U.S. state or federal laws.  The ends and means of private prediction markets differ materially from those of futures, securities, or gambling markets.  Laws written for those latter three institutions nonetheless threaten to limit or even outlaw private prediction markets.  As the paper details, however, careful legal engineering can protect private prediction markets from violating U.S. laws or suffering crushing regulatory burdens.  The paper concludes with a prediction about the likely form of potential CFTC regulations and a long-term strategy for ensuring the success of private prediction markets under U.S. law.

scholarly journals Regulation of Prediction Markets Under the Financial Markets Conduct Act 2013

2015 ◽  
Vol 46 (1) ◽  
pp. 137
Author(s):  
Kelsey Brooke Farmer
Keyword(s):  
New Zealand ◽  
Financial Markets ◽  
Regulatory Compliance ◽  
Recent History ◽  
Securities Markets ◽  
Prediction Markets ◽  
Prediction Market ◽  
Securities Law

The Financial Markets Conduct Act 2013 (FMC Act) represents the most substantial overhaul of New Zealand's securities law in recent history. The regulation of derivatives in particular featured high on the agenda as an area in need of reform and, as a result, the FMC Act is much more clear than the Securities Act 1978 and Securities Markets Act 1988 with respect to typical derivative agreements. The focus of this article, however, is on the atypical: the use of derivatives in prediction markets. This article examines whether New Zealand-based prediction market iPredict will be regulated under the FMC Act and, if so, how it will be regulated. The conclusion reached is that iPredict can operate under the FMC Act only if the Financial Markets Authority declares that its contracts are derivatives and grants substantial exemptions from regulatory compliance. This article then makes recommendations for a more coherent approach to the regulation of prediction markets by analogy with the new prescribed intermediary service licences under the FMC Act. 

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