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Optimal Risk Taking With Flexible Income

Jaksa Cvitanic
California Institute of Technology - Division of the Humanities and Social Sciences

Levon Goukasian
Pepperdine University - Business Division

Fernando Zapatero
University of Southern California - Marshall School of Business


January 11, 2007

AFA 2008 New Orleans Meetings Paper

Abstract:     
We study the portfolio selection problem of an investor who can optimally exert costly effort for more income. The possibility of generating more income, if necessary, increases the risk-taking appetite of the investor. We find the optimal allocation to the risky security as a proportion of financial wealth and as a proportion of the total wealth, defined as the combination of the financial wealth and the human capital of the investor. When the investor's objective is the maximization of the terminal wealth, we show that the optimal allocation to the risky security is a hump-shaped function of the investment horizon. However, when the investor maximizes utility from intertemporal consumption, the optimal allocation in the risky security is a constant proportion of the total wealth of the investor.

Keywords: Utility Maximization, Optimal Portfolio Selection, Optimal Effort

JEL Classifications: C61, G11

Working Paper Series

Date posted: March 09, 2006 ; Last revised: March 11, 2007

Suggested Citation

Cvitanic, Jaksa, Goukasian, Levon and Zapatero, Fernando, Optimal Risk Taking With Flexible Income (January 11, 2007). AFA 2008 New Orleans Meetings Paper. Available at SSRN: http://ssrn.com/abstract=887347


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Contact Information

Levon Goukasian (Contact Author)
Pepperdine University - Business Division ( email )
United States
Jaksa Cvitanic
California Institute of Technology - Division of the Humanities and Social Sciences ( email )
1200 East California Blvd.
Pasadena, CA 91125
United States
HOME PAGE: http://www.hss.caltech.edu/~cvitanic/
Fernando Zapatero
University of Southern California - Marshall School of Business ( email )
Los Angeles, CA 90089
United States
213-740-6538 (Phone)
213-740-6650 (Fax)
Feedback to SSRN (Beta)


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