Comparing trading behaviour and profit composition in prediction markets

2020 ◽  
Vol 14 (2) ◽  
pp. 3-26
Author(s):  
Martin Waitz ◽  
Andreas Mild
Keyword(s):  
Empirical Evidence ◽  
Classification Scheme ◽  
Prediction Markets ◽  
It Industry ◽  
Noise Traders ◽  
Prediction Market ◽  
Market Makers ◽  
Trading Behaviour

Prediction markets have established itself as forecasting technique, especially within the IT industry. While the majority of existing studies focuses either on the output of such markets or its design settings, the traders who actually produce the forecasts got only little attention yet. Within this work, we develop a classification scheme for traders of a prediction market that is grounded on both, financial and prediction market literature. Over a period of three years, 127 prediction markets have been observed and its 4.329 traders are separated into seven subgroups (beginners, noise traders, average traders, experts, donkey traders, market makers and superior traders), based on their knowledge, experience and selectivity. We find empirical evidence for the existence of these subgroups and thus for the heterogeneity among the traders. For each of these subgroups, we analyze the trading behaviour and the profit composition.

scholarly journals On the Observational Implications of Knightian Uncertainty

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kevin A. Hassett ◽  
Weifeng Zhong
Keyword(s):  
Empirical Evidence ◽  
Information Acquisition ◽  
Historical Data ◽  
Knightian Uncertainty ◽  
Prediction Markets ◽  
Prediction Market ◽  
The World ◽  
Betting Markets ◽  
Empirical Regularities

AbstractWe develop a model of a prediction market with ambiguity and derive testable implications of the presence of Knightian uncertainty. Our model can also explain two commonly observed empirical regularities in betting markets: the tendency for longshots to win less often than odds would indicate and the tendency for favorites to win more often. Using historical data from Intrade, we further present empirical evidence that is consistent with the predicted presence of Knightian uncertainty. Our evidence also suggests that, even with information acquisition, the Knightian uncertainty of the world may be not “learnable” to the traders in prediction markets.

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.

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. 

scholarly journals Prediction Markets – A literature review 2014

2014 ◽  
Vol 8 (2) ◽  
pp. 89-126 ◽  
Author(s):  
Christian Franz Horn ◽  
Bjoern Sven Ivens ◽  
Michael Ohneberg ◽  
Alexander Brem
Keyword(s):  
Literature Review ◽  
Classification Scheme ◽  
Prediction Markets ◽  
Comprehensive Review ◽  
Research Results ◽  
Law And Policy ◽  
Function Tests ◽  
Review 2014 ◽  
Number Of Publications

In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 304 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results are further compared to two previous works published by Zhao, Wagner and Chen (2008) and Tziralis and Tatsiopoulos (2007a). The article concludes with an extended bibliography section and may therefore serve as a guidance and basis for further research. (250 WORDS)

ARBITRAGE TRADE IN PREDICTION MARKETS

2013 ◽  
Vol 6 (3) ◽  
pp. 14-26
Author(s):  
O Bergfjord ◽  
P. Kildal ◽  
T.A. McPherson ◽  
L.R. Loftaas ◽  
K. Valvik
Keyword(s):  
Presidential Election ◽  
Prediction Markets ◽  
Prediction Market ◽  
Political Opinion ◽  
Arbitrage Opportunities ◽  
Political Events ◽  
The Us ◽  
Time Zones ◽  
Using Data

By using data from five similar prediction market (PM) contracts on the 2008 American presidential election in two different market places targeted at investors of different nationalities, we investigate whether arbitrage opportunities across borders and market places exist in these markets. We find that arbitrage opportunities are rare and difficult to exploit.  Markets in these political events seem to be fairly efficient, even if they are located in different countries, time zones and are relatively small. However, inter-market arbitrage opportunities exist, and we hypothesize that this can be explained by differences in political opinion between the US and other countries.

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