THE TRADESPORTS NFL PREDICTION MARKET: AN ANALYSIS OF MARKET EFFICIENCY, TRANSACTION COSTS, AND BETTOR PREFERENCES

2012 ◽  
Vol 2 (1) ◽  
pp. 45-71
Author(s):  
Philip O'Connor ◽  
Feng Zhou
Keyword(s):  
Transaction Costs ◽  
Market Efficiency ◽  
Trading Volume ◽  
Las Vegas ◽  
University Of California ◽  
Prediction Markets ◽  
Prediction Market ◽  
Computer Assistance ◽  
Point Spread ◽  
Line Point

We investigated 1,587 Tradesports point spread contracts for NFL games during the 2005/06 season. Differing point spreads create differing odds, meaning we could test for the traditional favorite long shot bias in NFL betting. We found that there was no favorite long shot bias. However, the market underestimated the chances of the favored team winning by about 10% across all odds categories, and this bias persisted throughout the season. We found relatively low transaction costs. For a price-taker, the Tradesports “Vegas-line” point spread had a 2.2% total takeout including exchange fees, about half of the 4.55% takeout of traditional legal bookmakers. Contracts with a price around 50, creating even money returns to bets on both teams, and higher volume contracts, had lower transaction costs. Participants were found to prefer the Las Vegas line point spread contract followed by the straight-up contract. Trading volume during the game (in-running) was about twice the trading volume leading up to the game. Teams with better season records and from cities with larger populations generated a higher volume of trades. Sunday night and Monday night games generated about four times more volume than regular Sunday games.Helpful comments were provided by Adi Schnytzer and participants of the 2007 University of California-Riverside Growth of Gambling and Prediction Markets Conference, and an excellent anonymous referee. We thank Jared Hunt for computer assistance.

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.

scholarly journals THE XBRL TECHNOLOGY AND MARKET EFFICIENCY IN BANKING COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE (IDX)

2020 ◽  
Vol 4 (1) ◽  
pp. 26
Author(s):  
Erni Jayani ◽  
Jumiadi Abdi Winata ◽  
Khairunnisa Harahap
Keyword(s):  
Information Asymmetry ◽  
Market Efficiency ◽  
Financial Reporting ◽  
Stock Prices ◽  
Trading Volume ◽  
Sampling Method ◽  
Stock Exchange ◽  
Institutional Ownership ◽  
Accurate Information ◽  
Stock Trading

The problem in this research is the need for fast and accurate information in the format of the presentation of financial statements resulting in the distribution of information, and data management can be problematic. Therefore, a format for financial reporting systems, namely Extensible Business Reporting Language (XBRL), was formed. The purpose of this study was to determine the effect of XBRL technology, stock prices, Return on Assets (ROA), and institutional ownership on market efficiency (information asymmetry and stock trading volume). The population and sample of this study are banking companies listed on the Indonesia Stock Exchange from 2015-2016. The sampling method using a purposive sampling method and obtained a sample of 42 companies. Data collection techniques are carried out by taking data from the Indonesia Stock Exchange website (www.idx.co.id) and the site http://finance.yahoo.com. Data were analyzed with multiple regression tests after being declared normal with the normality test and though using SPSS 20. The results of this study simultaneously stated that XBRL technology, stock prices, ROA, and institutional ownership together have an influence on information asymmetry and stock trading volume. From the results of the study, it can be concluded that XBRL technology, stock prices, ROA, and institutional ownership cause a decrease in the level of information asymmetry and trading volume. This result also states that the company is in excellent condition when the value of information asymmetry decreases, but it is not good when the trading volume of its shares also decreases. Keywords: XBRL Technology; Stock Prices; Market Efficiency; Information Asymmetry; Stock Trading Volume. 

Data Snooping on Technical Analysis: Evidence from the Taiwan Stock Market

2011 ◽  
Vol 14 (02) ◽  
pp. 195-212 ◽  
Author(s):  
Cheng-Wei Chen ◽  
Chin-Sheng Huang ◽  
Hung-Wei Lai
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Market Efficiency ◽  
Technical Analysis ◽  
The Other ◽  
Trading Rule ◽  
Data Snooping ◽  
Empirical Results

The main purpose of this paper is to investigate the validity and predictability of technical analysis in the Taiwan stock market. Bootstrapped tests of White (2000) and of Hansen (2005) are employed to ascertain whether there exists a superior trading rule among two broadly used sets of technical analysis. One coming from Brock et al. (1992) and the other from Sullivan et al. (1999). Moreover, this study brings together powerful bootstrapped tests along with two institutional adjustments to ascertain the efficacy of technical analysis: (1) non-synchronous trading and (2) transaction costs. The empirical results indicate that this triad-data snooping, non-synchronous trading and transaction costs, has a great impact on the performance of technical analysis. In fact, the Taiwan stock market stands for market efficiency, and economical profits cannot be rendered from technical analysis in this market.

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.

A THRESHOLD MODEL FOR STOCK RETURN VOLATILITY AND TRADING VOLUME

2000 ◽  
Vol 03 (03) ◽  
pp. 467-472 ◽  
Author(s):  
GIULIA IORI
Keyword(s):  
Transaction Costs ◽  
Trading Volume ◽  
Stock Return ◽  
Cross Correlation ◽  
Threshold Model ◽  
Feedback Mechanism ◽  
Return Volatility ◽  
Volatility Clustering ◽  
Stock Return Volatility ◽  
Future Trading

We propose a model with heterogeneous interacting traders which can explain the observed cross-correlation between stock return volatility and trading volume. Transaction costs are introduced which, by responding to price movements, create a feedback mechanism on future trading and generates volatility clustering.

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