A Monte Carlo Method for Optimal Portfolios

Abstract

Ce document est publié dans l'intention de rendre accessibles les résultats préliminaires de la recherche effectuée au CIRANO, afin de susciter des échanges et des suggestions. Les idées et les opinions émises sont sous l'unique responsabilité des auteurs, et ne représentent pas nécessairement les positions du CIRANO ou de ses partenaires. This paper presents preliminary research carried out at CIRANO and aims at encouraging discussion and comment. The observations and viewpoints expressed are the sole responsibility of the authors. They do not necessarily represent positions of CIRANO or its partners.

Stochastic dividend yields and derivatives pricing in complete markets

“…More precisely, we build on Detemple, Garcia, and Rindisbacher (2003) and Cvitanic, Goukasian, and Zapatero (2003) for the parameters of the underlying and the market price of risk while we use the empirical results of Campbell (2003) for the dividend yield. We therefore use the following basic set of data:…”

Numerical Solutions to Dynamic Portfolio Problems: The Case for Value Function Iteration using Taylor Approximation

“…Indeed, a large number of papers have recently appeared that employ approximation techniques to tackle challenging portfolio choice problems. These approaches include, among others, numerical solution of a partial differential equation as in Brennan et al (1997), log-linearization of the budget equation as in Campbell and Viceira (1999), state space discretization as in Balduzzi and Lynch (1999) and Barberis (2000), and, more recently, Malliavin calculus combined with Monte Carlo methods as in Detemple et al (2003). A comprehensive survey of the recent portfolio choice literature can be found in Brandt (2004).…”

A stochastic programming approach for multi-period portfolio optimization

“…This may be inappropriate for many investors. Detemple et al (2003) and Brandt et al (2005) use simulation-based approaches. Detemple et al approximate deviations from a closed-form solution, while Brandt et al provide an approach that is inspired by the option pricing algorithm by Longstaff and Schwartz (2001).…”