Portfolios and Risk Premia for the Long Run

Annals of Applied Probability, Forthcoming

Boston U. School of Management Research Paper No. 2011-4

38 Pages Posted: 18 Mar 2011 Last revised: 19 Jan 2012

See all articles by Paolo Guasoni

Paolo Guasoni

Boston University - Department of Mathematics and Statistics; Dublin City University - School of Mathematical Sciences; University of Bologna - Department of Statistics

Scott Robertson

Questrom School of Business, Boston University

Date Written: March 12, 2011

Abstract

This paper develops a method to derive optimal portfolios and risk premia explicitly in a general diffusion model, for an investor with power utility and a long horizon. The market has several risky assets and is potentially incomplete. Investment opportunities are driven by, and partially correlated with, state variables which follow an autonomous diffusion. The framework nests models of stochastic interest rates, return predictability, stochastic volatility and correlation risk.

In models with several assets and a single state variable, long-run portfolios and risk premia admit explicit formulas up the solution of an ordinary differential equation, which characterizes the principal eigenvalue of an elliptic operator. Multiple state variables lead to a quasilinear partial differential equation, which is solvable for many models of interest.

The paper derives the long-run optimal portfolio and the long-run optimal pricing measures depending on relative risk aversion, as well as their finite-horizon performance.

Keywords: Long Run, Portfolio Choice, Derivatives Pricing, Incomplete Markets

JEL Classification: G11

Suggested Citation

Guasoni, Paolo and Guasoni, Paolo and Robertson, Scott, Portfolios and Risk Premia for the Long Run (March 12, 2011). Annals of Applied Probability, Forthcoming, Boston U. School of Management Research Paper No. 2011-4, Available at SSRN: https://ssrn.com/abstract=1784436

Paolo Guasoni (Contact Author)

Boston University - Department of Mathematics and Statistics ( email )

Boston, MA 02215
United States

Dublin City University - School of Mathematical Sciences ( email )

Dublin
Ireland

HOME PAGE: http://www.guasoni.com

University of Bologna - Department of Statistics ( email )

Bologna, 40126
Italy

Scott Robertson

Questrom School of Business, Boston University ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
295
Abstract Views
1,837
Rank
156,697
PlumX Metrics