Estimating Allocations for Value-at-Risk Portfolio Optimzation

24 Pages Posted: 25 Oct 2007

See all articles by Abder Oulidi

Abder Oulidi

IMA-UCO

Arthur Charpentier

Université du Québec à Montréal; Université du Québec à Montréal

Date Written: August 28, 2007

Abstract

Value-at-Risk, despite being adopted as the standard risk measure in finance, but suffers severe objections from a practical point of vue, due to a lack of convexity, and since it does not reward diversification (which is an essential feature in portfolio optimization). Furthermore, it is also known as having poor behavior in risk estimation (which has been justified to impose the use of parametric models, but which induces then model errors). The aim of this paper is to chose in favour or against the use of VaR but to add some more information to this discussion, especially from the estimation point of view. Here we propose a simple method not only to estimate the optimal allocation based on a Value-at-Risk minimization constraint, but also to derive - empirical - confidence intervals based on the fact that the underlying distribution is unkown, and can be estimated based on past observations.

Keywords: nonparametric estimation, optimal allocations, Value-at-Risk

Suggested Citation

Oulidi, Abder and Charpentier, Arthur, Estimating Allocations for Value-at-Risk Portfolio Optimzation (August 28, 2007). Available at SSRN: https://ssrn.com/abstract=1023911 or http://dx.doi.org/10.2139/ssrn.1023911

Abder Oulidi (Contact Author)

IMA-UCO ( email )

place André Leroy
Angers, 49000
France

Arthur Charpentier

Université du Québec à Montréal ( email )

PB 8888 Station DownTown
Succursale Centre Ville
Montreal, Quebec H3C3P8
Canada

Université du Québec à Montréal ( email )

Canada

HOME PAGE: http://https://freakonometrics.github.io/

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