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Consumption-Portfolio Optimization with Recursive Utility in Incomplete Markets


Holger Kraft


Goethe University Frankfurt

Frank Thomas Seifried


University of Kaiserslautern

Mogens Steffensen


University of Copenhagen

June 26, 2011


Abstract:     
In an incomplete market we study the optimal consumption-portfolio decision of an investor with recursive preferences of Epstein-Zin type. Applying a classical dynamic programming approach, we formulate the associated Hamilton-Jacobi-Bellman equation and provide a suitable verification theorem. The proof of this verification theorem is complicated by the fact that the Epstein-Zin aggregator is non-Lipschitz, so standard verification results (e.g., in Duffie and Epstein (1992)) are not applicable. We provide new explicit solutions to the Bellman equation with Epstein-Zin preferences in an incomplete market for non-unit EIS and apply our verification result to prove that they solve the consumption-investment problem. We also compare our exact solutions to the Campbell-Shiller approximation and assess its accuracy.

Number of Pages in PDF File: 32

Keywords: consumption-portfolio optimization, recursive utility, stochastic control approach, stochastic volatility, unspanned state process, Campbell-Shiller approximation

JEL Classification: G11, D91, C61

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Date posted: June 3, 2010 ; Last revised: June 28, 2011

Suggested Citation

Kraft, Holger, Seifried, Frank Thomas and Steffensen, Mogens, Consumption-Portfolio Optimization with Recursive Utility in Incomplete Markets (June 26, 2011). Available at SSRN: http://ssrn.com/abstract=1619141 or http://dx.doi.org/10.2139/ssrn.1619141

Contact Information

Holger Kraft (Contact Author)
Goethe University Frankfurt ( email )
Faculty of Economics and Business Administration
Grueneburgplatz 1
Frankfurt am Main, 60323
Germany
Frank Thomas Seifried
University of Kaiserslautern ( email )
Erwin-Schrödinger-Straße
67663 Kaiserslautern
Germany
+49-631-2054483 (Phone)
HOME PAGE: http://www.mathematik.uni-kl.de/~seifried
Mogens Steffensen
University of Copenhagen ( email )
Universitetsparken 5
DK-2100 Copenhagen
Denmark
Feedback to SSRN (Beta)


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