Integrating Market Makers, Limit Orders, and Continuous Trade in Prediction Markets

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.

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THE HIDDEN BEAUTY OF THE QUADRATIC MARKET SCORING RULE: A UNIFORM LIQUIDITY MARKET MAKER, WITH VARIATIONS

The Journal of Prediction Markets ◽

10.5750/jpm.v1i2.423 ◽

2012 ◽

Vol 1 (2) ◽

pp. 111-125 ◽

Cited By ~ 2

Author(s):

Michael Abramovicz

Keyword(s):

Scoring Rules ◽

Prediction Markets ◽

Market Maker ◽

Scoring Rule ◽

Market Makers ◽

Market Participants ◽

Aggregate Information ◽

Spectrum Market

For some applications, prediction markets that rely entirely on voluntary transactions between individual participants may provide insufficient liquidity to aggregate information effectively, especially where the number of participants is small. A solution to this problem is to rely on an automated market maker, which allows participants to buy from or sell to the house. Robin Hanson has described a class of automated market makers called market scoring rules. This Article examines a member of this class that has received little attention, the quadratic market scoring rule. Its prime virtue is that it provides uniform liquidity across the probability or prediction spectrum. Market participants will thus have the same incentive to do research that is expected to produce an expected change in the market prediction, regardless of the current prediction. Formulas are provided for implementing the quadratic market scoring rule, as well as variations, for example to implement conditional markets.

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Comparing trading behaviour and profit composition in prediction markets

The Journal of Prediction Markets ◽

10.5750/jpm.v14i2.1561 ◽

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.

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An empirical examination of the relationship between naked shorting and share prices around the announcement of a firm’s need for external capital

Journal of Governance and Regulation ◽

10.22495/jgr_v1_i4_c1_p3 ◽

2012 ◽

Vol 1 (4) ◽

pp. 139-164

Author(s):

Austin Murphy ◽

Hong Qian ◽

Yun Zhu ◽

Ranadeb Chaudhuri

Keyword(s):

Negative Impact ◽

External Financing ◽

Empirical Examination ◽

Equity Prices ◽

Share Prices ◽

Delayed Effects ◽

Market Makers ◽

Limit Orders ◽

Equity Value ◽

Significant Negative Impact

This research finds some empirical evidence that the sale of stock without delivering shares can contribute to pressuring down the equity prices of companies seeking to raise capital. By allowing for the delayed effects on prices of limit orders by naked shorts, a significant negative impact on equity value per share is discovered but only for naked short selling by market makers and only on stocks of firms in urgent need of external financing.

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A Simple Automated Market Maker for Prediction Markets

The Oxford Handbook of the Economics of Gambling ◽

10.1093/oxfordhb/9780199797912.013.0028 ◽

2013 ◽

pp. 541-559

Author(s):

David Johnstone

Keyword(s):

Behavioral Finance ◽

Prediction Markets ◽

Market Maker ◽

Price Setting ◽

Simulation Games ◽

Prior Beliefs ◽

Over The Counter ◽

Market Makers ◽

Market Simulation ◽

Betting Markets

There is wide scope for reliance on automated “robot” market makers in prediction markets and market simulation games in experimental economics and behavioral finance. The market maker presented here is an alternative to the well-known but less easily understood Hanson market maker. It has the advantage of being easy to derive and makes a good mathematical introduction to the logic of automated bid and ask price–setting in prediction markets. Its main advantage is that the opening security price can be set arbitrarily between zero and one, so as to match the market maker’s prior beliefs. A weakness of the Hanson market maker is that it opens automatically with a uniform prior distribution. In many real-world applications, this is unrealistic and prone to cause the market maker unnecessary trading losses (on average). Common practice, such as in betting markets and over-the-counter financial markets for binaries, is to set opening prices based on expert subjective probabilities.

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How much market making does a market need?

Journal of Applied Probability ◽

10.1017/jpr.2018.44 ◽

2018 ◽

Vol 55 (3) ◽

pp. 667-681

Author(s):

Vít Peržina ◽

Jan M. Swart

Keyword(s):

Equilibrium Distribution ◽

Limit Order Book ◽

Walrasian Equilibrium ◽

Order Book ◽

Limit Order ◽

Demand And Supply ◽

Market Makers ◽

Limit Orders ◽

Bid Price ◽

Random Level

AbstractWe consider a simple model for the evolution of a limit order book in which limit orders of unit size arrive according to independent Poisson processes. The frequencies of buy limit orders below a given price level, respectively sell limit orders above a given level, are described by fixed demand and supply functions. Buy (respectively, sell) limit orders that arrive above (respectively, below) the current ask (respectively, bid) price are converted into market orders. There is no cancellation of limit orders. This model has been independently reinvented by several authors, including Stigler (1964), and Luckock (2003), who calculated the equilibrium distribution of the bid and ask prices. We extend the model by introducing market makers that simultaneously place both a buy and sell limit order at the current bid and ask price. We show that introducing market makers reduces the spread, which in the original model was unrealistically large. In particular, we calculate the exact rate at which market makers need to place orders in order to close the spread completely. If this rate is exceeded, we show that the price settles at a random level that, in general, does not correspond to the Walrasian equilibrium price.

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Chasing Private Information

Review of Financial Studies ◽

10.1093/rfs/hhz029 ◽

2019 ◽

Vol 32 (12) ◽

pp. 4997-5047 ◽

Cited By ~ 11

Author(s):

Marcin Kacperczyk ◽

Emiliano S Pagnotta

Keyword(s):

Private Information ◽

Option Markets ◽

Market Makers ◽

Oxford University ◽

Limit Orders ◽

Private Signals ◽

Reward Program ◽

Editorial Decision ◽

Event Uncertainty ◽

Bid Ask Spreads

Abstract Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bid-ask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns. Received January 11, 2017; editorial decision December 17, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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Large Option Trades, Market Makers, and Limit Orders

Review of Financial Studies ◽

10.1093/rfs/9.3.977 ◽

1996 ◽

Vol 9 (3) ◽

pp. 977-1002 ◽

Cited By ~ 23

Author(s):

Henk Berkman

Keyword(s):

Market Makers ◽

Limit Orders

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