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Research of Stock Price Manipulation Controlling System Based on Multi-Agent

Author: ZhuCheng
Tutor: HuDaiPing
School: Shanghai Jiaotong University
Course: Management Science and Engineering
Keywords: Stock price manipulation Multi-Agent Technology Regulatory system Q-learning algorithm Functional modules
CLC: TP319
Type: Master's thesis
Year: 2009
Downloads: 77
Quote: 1
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Abstract


On stock market investments, stock manipulation traditionally abhor the behavior of investors, have a negative impact on the stock market, but also undermine investors' confidence. Because of the particularity of stock price manipulation, regulatory agencies and the market for stock price manipulation regulatory lag and is not comprehensive, it is necessary to introduce intelligence technology to the field of regulation. Multi-Agent technology due to the maturity of its intelligence and its development, supervision by their intelligence and learning, with the development of the market and continue to optimize. An effort to reach in time to stop the manipulation and mitigate the consequences of manipulation purposes. So far, Agent technology has been involved in the stock area, but its main focus on system operation smart management, stock prediction and simulation of the securities market, simulation and empirical studies, yet involved in stock regulators, especially the stock price manipulation regulatory . The one hand, due to changes in the stock market is too large, some difficulties in the application of agent technology, on the other hand is still rare, the stock price manipulation aspects of the research focuses on modeling and simulation analysis to manipulate behavior and consequences because the stock price manipulation algorithms, while due to the variability of the stock market is too large, the stock price manipulation algorithm has not yet formed a system. This article efforts to achieve this through the use of Multi-Agent system of intelligent, autonomous structure and objectives. First, the overall analysis of stock price manipulation of the regulatory system, the design of the monitoring process, regulatory feedback, learning algorithm training, information state maintenance, and the results of the query five functional modules. Based on this, the design goals of the regulatory system. And initially completed the composition of its detailed internal structure of Multi-Agent system design. Completed the initial analysis of system development and design work. Secondly, in the 5 function module based on system design based on the detailed design of the system's database, the operation timing and interface. Clearly defines the attributes of the database table to establish the operation timing process and operator interface window. Meanwhile, based on the regulatory status quo and the theoretical basis of share price manipulation, initially established regulatory methods, combined from the price point of view and from the account angle and the regulatory system of the system itself, and at the same time and set up a system of weights . Agent learning methods, this paper uses a Q-learning algorithm method, system intelligent learning through Q-learning method to find the optimal false negative rate and the false positive rate. Finally, the overall realization of the initial system design goals, C Builder software and database systems major functional modules run by directly setting the text, and introduce instant data capture, data feedback and storage capabilities concrete realization process and code . This study stock price manipulation regulatory intelligent and automated some exploration and research, and a little new thinking based on the research status. Certain reference value for the use and implementation of future stock price manipulation of the regulatory system.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Specific applications
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