JMF  Vol.8 No.1 , February 2018
Mathematical Model of Financial Investment Risk
Author(s) Deyu Yin
ABSTRACT
This paper establishes the income and risk model in financial investment based on multi-objective programming theory, aiming to analyze the relationship between risk and return in financial investment and discuss the relationship between the risk the investor shall bear and decentralization degree of investment project. MATLAB software is used to analyze the investor’s optimized return under fixed risk level and the minimized risk with defined benefit. In addition, it chooses the optimal portfolio under such risk level with respect to the bearing capacity of different risks. This paper performs sensitivity analysis of risk in income model using LINGO software, and puts forward the optimal portfolio for the investor without special preference. Calculations show that the model established is satisfactory in determining the optimal portfolio.
Cite this paper
Yin, D. (2018) Mathematical Model of Financial Investment Risk. Journal of Mathematical Finance, 8, 127-136. doi: 10.4236/jmf.2018.81011.
References
[1]   Chen, Y.H., Xu, L. and Wang, X.G. (2000) Application of DEA in Risk Investment Project Decision. Science-Technology and Management.

[2]   Peng, S.K. (2000) Capital Asset Pricing Model and Risk Project Evaluation. Forecasting.

[3]   Yan, T.H. and Zhang, L. (2002) Analysis and Comparison of Risk Investment Project Pricing Methods. China Economist, No. 11.

[4]   Vance, H. and Robert, D. (1994) Toward a Model of Venture Capital Investment Decision Making. Financial Management, 23, 8-37

[5]   Trester, J.J. (1998) Venture Capital Contracting under Asymmetric Information Journal of Banking & Finance, 22, 675-699.

[6]   Li, D. (1982) Operational Research. Tsinghua University Press, Beijing.

[7]   Zhou, H.L. (1995 Linear Programming and Its Application. Metallurgical Industry Press.

[8]   Wang, J.F. (2000) Venture Investment Practice and Cases. Tsinghua University Press, Beijing.

[9]   Wu, S.S. (1998) Application of Mathematical Method in Analysis of Financial Investment Risk. Journal of Huaqiao University (Humanities & Social Science), No. 1.

[10]   Krishnamurthy, P.K., Fisher, J.B. and Johnson, C. (2010) Mainstreaming Local Perceptions of Hurricane Risk into Policymaking: A Case Study of Community GIS in Mexico. Global Environmental Change, No. 1.

[11]   Fan, Y.L., Ginis, I., Hara, T., Wright, C.W. and Walsh, E.J. (2009) Numerical Simulations and Observations of Surface Wave Fields under an Extreme Tropical Cyclone. Journal of Physical Oceanography, No. 9.

[12]   Vickery, P.J., Wadhera, D., Powell, M.D. and Chen, Y.Z. (2009) A Hurricane Boundary Layer and Wind Field Model for Use in Engineering Applications. Journal of Applied Meteorology and Climatology, No. 2.

[13]   Liu, X.Z. and Li, J.Z. (2008) Application of SCS Model in Estimation of Runoff from Small Watershed in Loess Plateau of China. Chinese Geographical Science, No. 3.

 
 
Top