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Investment Risk Evaluation Model Research Based on Improved Genetic Neural Network

Author: HeQiang
Tutor: LiuTieYing
School: Inner Mongolia University
Course: Management Science and Engineering
Keywords: Venture Capital Risk assessment Benefit assessment Index system Genetic Neural Network
CLC: F831.6
Type: Master's thesis
Year: 2010
Downloads: 189
Quote: 2
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Abstract


Every moment with the growing impact of the financial crisis on the global economic development , venture capital is full of risks , its impact on the economic development of deeper and deeper . Therefore , the scientific assessment of the risks of investing has become a necessary subject to the risk of the investment process . In order to reduce the risk of investment loss , we are very necessary to take reasonable and effective way to develop a scientific and comprehensive evaluation system . Only then will we be able to risk in the investment decision-making , strategizing, in order to promote the development of high-tech , and ultimately to promote the sound and rapid development of the national economy . Currently, the model commonly used in risk investment evaluation and decision making : risk assessment techniques , AHP (Analytic Hierarchy Process) Analytic Hierarchy Process , portfolio risk assessment model , the linear programming model . These model for risk investment decision-making tools and ideas at the same time , were also limitations . In this paper, based on the results of previous studies , through the use of dynamic artificial intelligence algorithms to establish evaluation model and adding investor investment preference factor to correct the results of the assessment , scientific decision-making in order to achieve the purpose . This paper first introduces the great significance of the risk of the investment on the development of the national economy , and then analyzes the operation mechanism of risk investment evaluation and its characteristics, as well as the risk of investment in the application of existing models and methods of assessment decisions limitations ; Finally, through experiments , surveys combined see risk investment evaluation criteria and other literature methods to build the venture capital evaluation system . In this process, the focus on the assessment of the risk of investment , improved genetic neural network algorithm for superior performance , as well as the venture capital model of risk assessment and effective assessment of both risk investment decision analysis problems . Through in-depth research , this paper presents a dynamic factors , investors can be based on the preferences of the risk - benefit scientific decision-making methods . Finally , in the MATLAB R2009a environmental program , to build the venture capital model testing and validation examples . The empirical results show that the improved genetic neural network algorithm effectively improve the operation efficiency of the algorithm and improved the accuracy and reasonableness of the risk assessment system .

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CLC: > Economic > Fiscal, monetary > Finance, banking > World of finance, banking > International financial relations
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