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Research on Strategic Analysis and Decision Modeling of Venture Portfolio
Journal of Investment and Management
Volume 7, Issue 3, June 2018, Pages: 91-101
Received: Aug. 9, 2018; Published: Aug. 13, 2018
Views 1104      Downloads 96
Authors
Liu Xiaobing, College of Management, Shenzhen University, Shenzhen, China; Research Centre on Fictitious Economy and Data Science, University of Chinese Academy of Sciences, Beijing, China
Tian Yingjie, Research Centre on Fictitious Economy and Data Science, University of Chinese Academy of Sciences, Beijing, China
Liu Manhong, Finance School, Renmin University, Beijing, China
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Abstract
The value of risk project is usually uncertain, so venture investor must make investment decision based on prior estimation of future value of risk projects. This paper constructs a portfolio optimization model of risk projects considering the psychological characteristics of venture investors, and proposes a Bayesian method to deal with the uncertainty of value estimation in project portfolio selection, and utilizes Monte Carlo method to simulate the model as a linear integer programming problem. The study finds that, compared with portfolio selection based directly on ex ante value estimation, Bayesian modeling of project estimates of project value uncertainty can provide more accurate value estimates and use the resulting revised estimates to make portfolio decisions can help to select a project portfolio with a higher expected utility, eliminate the expected interval between the expected pre-expected utility and the expected utility of post-implementation, and reduce the degree of disappointment of venture investor's expected decision-making.
Keywords
Project Portfolio, Loss Disgust, Bayes Modeling, Strategic Analysis
To cite this article
Liu Xiaobing, Tian Yingjie, Liu Manhong, Research on Strategic Analysis and Decision Modeling of Venture Portfolio, Journal of Investment and Management. Vol. 7, No. 3, 2018, pp. 91-101. doi: 10.11648/j.jim.20180703.14
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