Price Manipulation in an Experimental Asset Market (original) (raw)
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Price Manipulation in an Experimental Asset Market RM/06/024
arno.unimaas.nl
We analyze in the laboratory whether an uninformed trader is able to manipulate the price of a financial asset. To do so, we compare the results of two different experimental treatments. In the Benchmark Treatment, twelve subjects trade a common value asset that takes either a high or a low value. Information is distributed asymmetrically, only three out of twelve subjects know the actual value of the asset. The Manipulation Treatment is identical to the Benchmark Treatment apart from the fact that we introduce a computer program as an additional trader. This manipulation program buys a fixed number of shares in the beginning of a trading period and sells them afterwards again. Our results show that the last contract price is significantly higher in the Manipulation Treatment if the asset takes a low value and that there are no price differences between the two treatments if the value of the asset is high. Moreover, this simple manipulation program is, at least in some instances, profitable.
Documentos de trabajo (FEDEA), 2008
We study with the help of a laboratory experiment the conditions under which an uninformed manipulator -a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on -is able to induce higher asset prices. We find that the average contract price is significantly higher in the presence of the manipulator if, and only if, the asset takes the lowest possible value and insiders have perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains; i.e., independently on whether the informed traders have perfect or partial information, it earns always more than the average trader. Finally, not only uninformed subjects suffer from the presence of the robot trader, but also some of the imperfectly informed insiders have lower payoffs once the robot trader is added as a market participant.
Information aggregation in experimental asset markets in the presence of a manipulator
Documentos de trabajo (FEDEA), 2008
We study with the help of a laboratory experiment the conditions under which an uninformed manipulator - a robot trader that unconditionally buys several shares of a common value asset in the beginning of a trading period and unwinds this position later on - is able to induce higher asset prices. We find that the average contract price is significantly higher in the presence of the manipulator if, and only if, the asset takes the lowest possible value and insiders have perfect information about the true value of the asset. It is also evidenced that the robot trader makes trading gains; i.e., independently on whether the informed traders have perfect or partial information, it earns always more than the average trader. Finally, not only uninformed subjects suffer from the presence of the robot trader, but also some of the imperfectly informed insiders have lower payoffs once the robot trader is added as a market participant.
Information Aggregation and Manipulation in an Experimental Market
2004
Prediction markets are increasingly being considered as methods for gathering, summarizing and aggregating diffuse information by governments and businesses alike. Critics worry that these markets are susceptible to price manipulation by agents who wish to distort decision making. We study the effect of manipulators on an experimental market. We find that manipulators are unable to distort price accuracy. Subjects without manipulation incentives compensate for the bias in offers from manipulators by setting a different threshold at which they are willing to accept trades. * The authors thank Manuela Abbate for research assistance and an anonymous referee for helpful comments. We gratefully acknowledge the financial support of the International Foundation for Research in Experimental Economics.
Using agent-based artificial financial market to analyse market manipulation
2018
This work aims to evaluate price manipulation provided by investors with great amount of capital and its overall effect in the stock market. In order to do so, we have created an artificial financial market using NetLogo. The experiments were carried out in a closed environment, with technical analysis speculators and other three different groups of agents, each one with a unique investment strategy. This work provides inputs for the creation of an artificial financial market, in which other diverse agent strategies could be added, and evidences of a market manipulation caused by excess demand. Resumo. Este trabalho visa estudar a manipulação de preços por grandes investidores e seu efeito geral no mercado de ações.. Para isto, criou-se um mercado financeiro artificial utilizando NetLogo. Foram efetuados experimentos em um ambiente fechado, com especuladores que utilizam análise técnica e outros três diferentes perfis de agentes com estratégias de investimento únicas. Este trabalho ...
Manipulation in Conditional Decision Markets
Group Decision and Negotiation, 2017
Conditional decision markets concurrently predict the future and decide on it. These markets price the impact of decisions, conditional on them being executed. After the markets close, a principal decides which decisions are executed based on the prices in the markets. As some decisions are not executed, the respective outcome cannot be observed, and the markets predicting the impact of non-executed decisions are void. This allows ex-post costless manipulation of such markets. We conduct two versions of an online experiment to explore scenarios in which a principal runs conditional decision markets to inform her choice among a set of a risky alternatives. We find that the level of manipulation depends on the simplicity of the market setting. When a trader is alone, has the power to move prices far enough, and the decision is deterministically tied to market prices or a very high correlation between prices and decision is implied, only then manipulation occurs. As soon as another trader is present to add risk to manipulation, manipulation is eliminated. Our results contrast theoretical work on conditional decision markets in two ways: First, our results suggest Electronic supplementary material The online version of this article (
Characterising trader manipulation in a limit-order driven market
Mathematics and Computers in Simulation, 2013
Use of trading strategies to mislead other market participants, commonly termed trade-based market manipulation, has been identified as a major problem faced by present day stock markets. Although some mathematical models of trade-based market manipulation have been previously developed, this work presents a framework for manipulation in the context of a realistic computational model of a limit-order market. The Maslov limit order market model is extended to introduce manipulators and technical traders. We show that "pump and dump" manipulation is not possible with traditional Maslov (liquidity) traders. The presence of technical traders, however, makes profitable manipulation possible. When exploiting the behaviour of technical traders, manipulators can wait some time after their buying phase before selling, in order to profit. Moreover, if technical traders believe that there is an information asymmetry between buy and sell actions, the manipulator effort required to perform a "pump and dump" is comparatively low, and a manipulator can generate profits even by selling immediately after raising the price.
Stock Market Manipulation on the Hong Kong Stock Exchange
Australasian Accounting, Business and Finance Journal, 2014
This study is the first to empirically examine stock market manipulation on the Hong Kong Stock Exchange. The dataset contains 40 cases of market manipulation from 1996 to 2009 that were successfully prosecuted by the Hong Kong Securities & Futures Commission. Manipulation is found to negatively impact market efficiency measures such as the bid-ask spread and volatility. Markets appear incapable of efficiently responding to the presence of manipulators and are characterised by information asymmetry. Manipulators were successfully able to raise prices and exit the market. This finding contradicts views that trade-based manipulation is entirely unprofitable and self-deterring. The victimisation of information-seeking investors and the market as a whole provides a strong rationale for all jurisdictions, including Australia, to have effective laws that prohibit manipulation and for robust enforcement of those laws to further deter market manipulation.
Noise Trading in a Laboratory Financial Market: A Maximum Likelihood Approach
Journal of the European Economic Association, 2005
We study the extent to which, in a laboratory …nancial market, noise trading can stem from subjects' irrationality. We estimate a structural model of sequential trading by using experimental data. In the experiment, subjects receive private information on the value of an asset and trade it in sequence with a market maker. We …nd that, in the laboratory, the noise due to the irrational use of private information Acknowledgements: We gratefully acknowledge the …nancial support of the