Characterising trader manipulation in a limit-order driven market
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. (c) 2012 IMACS. Published by Elsevier B.V. All rights reserved.
market manipulation limit order markets market micro-structure models bayesian learning