ON MARKET MAKER FUNCTIONS

2012 ◽  
Vol 3 (1) ◽  
pp. 61-63 ◽  
Author(s):  
Robin Hanson
Keyword(s):  
Scoring Rules ◽  
Double Auction ◽  
Market Maker ◽  
Main Function ◽  
Market Makers ◽  
Continuous Double Auction

Since market scoring rules have become popular as a form of market maker, it seems worth reviewing just what such mechanisms are intended to do.The main function performed by most market makers is to serve as an intermediary between people who prefer to trade at different times.  Traders who have the same favorite times to trade can show up together to an ordinary continuous double auction, and then make and accept offers to trade.  But when traders have different favorite times, a market maker can help them by first making offers that some of them will accept, and then later making opposite offers which others will accept.  By adjusting prices in his favor, a market maker can even profit from providing this service.

Liquidity Provision and Cross Arbitrage in Continuous Double-Auction Prediction Markets

2014 ◽  
Vol 7 (3) ◽  
pp. 61-86
Author(s):  
Werner Antweiler
Keyword(s):  
Stock Market ◽  
Empirical Analysis ◽  
Double Auction ◽  
Prediction Markets ◽  
Market Maker ◽  
Micro Structure ◽  
Liquidity Provision ◽  
Novel Method ◽  
Continuous Double Auction ◽  
Bid Ask Spreads

Continuous double-auction prediction markets often exhibit low transaction volume due to substantial bid-ask spreads. This paper explores a novel method of providing artificial liquidity in continuous double-auction prediction markets by introducing an automated market maker that engages in zero-profit cross-arbitrage in multi-contract markets. Empirical analysis of observed bid-ask spreads, liquidity, offer acceptance, and order sizes in the 2008 UBC Election Stock Market provides additional new insights into the micro-structure of prediction markets. 

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

2012 ◽  
Vol 1 (2) ◽  
pp. 111-125 ◽  
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.

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.

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