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Research and Application of Data Mining in Securities Investment Cost Analysis

Author: YuYongJun
Tutor: JiangHong
School: East China Normal University
Course: Computer technology
Keywords: Data Mining Trading Cost Impact Cost Logistic Regression Empirical Distribution Trading Optimization Securities Investment
CLC: F224
Type: Master's thesis
Year: 2010
Downloads: 120
Quote: 0
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Abstract


The security market is so dynamic that there are many participants to make numerous transactions with large amount of capital everyday, which generates thousands of data as well. Thus data mining technology, with its advantage on data analysis, is gradually conducted in data analysis of bond market to provide decision support for the investors. Among all the participants, although the quantity of institutional investor is not a big number, but the total transaction amount is numerous. The transaction cost then becomes a critical factor to be evaluated during the investment. The control of transaction cost will seriously impact on the return of investment.According to the analysis, it’s found that there is a big proportion of the cost only coming from a small quantity of transaction. This article is trying to analyze the transaction data through data mining and help find out those stocks that generates the high transaction cost through the logistic regression and empirical distribution’s probability taxonomic approachFurthermore, this article explored the process of the transaction execution and analyzed the most important part of transaction cost-market impact cost, to dig out the key factor that impacts the cost and establish the forecast modeling of market impact cost. When apply the modeling to optimize the transaction, it’s proved to achieve better result.

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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