Research on Strategic Analysis and Decision Modeling of Venture Portfolio

Liu Xiaobing; Tian Yingjie; Liu Manhong

doi:doi:10.11648/j.jim.20180703.14

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Research on Strategic Analysis and Decision Modeling of Venture Portfolio

Liu Xiaobing, Tian Yingjie, Liu Manhong

Published in Journal of Investment and Management (Volume 7, Issue 3)

Received: 9 August 2018 Published: 13 August 2018

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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.

Published in	Journal of Investment and Management (Volume 7, Issue 3)
DOI	10.11648/j.jim.20180703.14
Page(s)	91-101
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Project Portfolio, Loss Disgust, Bayes Modeling, Strategic Analysis

References

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APA Style

Liu Xiaobing, Tian Yingjie, Liu Manhong. (2018). Research on Strategic Analysis and Decision Modeling of Venture Portfolio. Journal of Investment and Management, 7(3), 91-101. https://doi.org/10.11648/j.jim.20180703.14

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ACS Style

Liu Xiaobing; Tian Yingjie; Liu Manhong. Research on Strategic Analysis and Decision Modeling of Venture Portfolio. J. Invest. Manag. 2018, 7(3), 91-101. doi: 10.11648/j.jim.20180703.14

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AMA Style

Liu Xiaobing, Tian Yingjie, Liu Manhong. Research on Strategic Analysis and Decision Modeling of Venture Portfolio. J Invest Manag. 2018;7(3):91-101. doi: 10.11648/j.jim.20180703.14

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@article{10.11648/j.jim.20180703.14,
  author = {Liu Xiaobing and Tian Yingjie and Liu Manhong},
  title = {Research on Strategic Analysis and Decision Modeling of Venture Portfolio},
  journal = {Journal of Investment and Management},
  volume = {7},
  number = {3},
  pages = {91-101},
  doi = {10.11648/j.jim.20180703.14},
  url = {https://doi.org/10.11648/j.jim.20180703.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jim.20180703.14},
  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.},
 year = {2018}
}

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TY  - JOUR
T1  - Research on Strategic Analysis and Decision Modeling of Venture Portfolio
AU  - Liu Xiaobing
AU  - Tian Yingjie
AU  - Liu Manhong
Y1  - 2018/08/13
PY  - 2018
N1  - https://doi.org/10.11648/j.jim.20180703.14
DO  - 10.11648/j.jim.20180703.14
T2  - Journal of Investment and Management
JF  - Journal of Investment and Management
JO  - Journal of Investment and Management
SP  - 91
EP  - 101
PB  - Science Publishing Group
SN  - 2328-7721
UR  - https://doi.org/10.11648/j.jim.20180703.14
AB  - 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.
VL  - 7
IS  - 3
ER  -

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Author Information

Liu Xiaobing

College of Management, Shenzhen University, Shenzhen, 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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APA Style

Liu Xiaobing, Tian Yingjie, Liu Manhong. (2018). Research on Strategic Analysis and Decision Modeling of Venture Portfolio. Journal of Investment and Management, 7(3), 91-101. https://doi.org/10.11648/j.jim.20180703.14

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ACS Style

Liu Xiaobing; Tian Yingjie; Liu Manhong. Research on Strategic Analysis and Decision Modeling of Venture Portfolio. J. Invest. Manag. 2018, 7(3), 91-101. doi: 10.11648/j.jim.20180703.14

Copy | Download

AMA Style

Liu Xiaobing, Tian Yingjie, Liu Manhong. Research on Strategic Analysis and Decision Modeling of Venture Portfolio. J Invest Manag. 2018;7(3):91-101. doi: 10.11648/j.jim.20180703.14

Copy | Download

@article{10.11648/j.jim.20180703.14,
  author = {Liu Xiaobing and Tian Yingjie and Liu Manhong},
  title = {Research on Strategic Analysis and Decision Modeling of Venture Portfolio},
  journal = {Journal of Investment and Management},
  volume = {7},
  number = {3},
  pages = {91-101},
  doi = {10.11648/j.jim.20180703.14},
  url = {https://doi.org/10.11648/j.jim.20180703.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jim.20180703.14},
  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.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Research on Strategic Analysis and Decision Modeling of Venture Portfolio
AU  - Liu Xiaobing
AU  - Tian Yingjie
AU  - Liu Manhong
Y1  - 2018/08/13
PY  - 2018
N1  - https://doi.org/10.11648/j.jim.20180703.14
DO  - 10.11648/j.jim.20180703.14
T2  - Journal of Investment and Management
JF  - Journal of Investment and Management
JO  - Journal of Investment and Management
SP  - 91
EP  - 101
PB  - Science Publishing Group
SN  - 2328-7721
UR  - https://doi.org/10.11648/j.jim.20180703.14
AB  - 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.
VL  - 7
IS  - 3
ER  -

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