Paper Info
Title
Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization
Abstract
Value-at-Risk (VaR) is one of the most widely accepted risk measures in the financial and insurance industries, yet efficient optimization of VaR remains a very difficult problem. We propose a computationally tractable approximation method for minimizing the VaR of a portfolio based on robust optimization techniques. The method results in the optimization of a modified VaR measure, Asymmetry-Robust VaR (ARVaR), that takes into consideration asymmetries in the distributions of returns and is coherent, which makes it desirable from a financial theory perspective. We show that ARVaR approximates the Conditional VaR of the portfolio as well. Numerical experiments with simulated and real market data indicate that the proposed approach results in lower realized portfolio VaR, better efficient frontier, and lower maximum realized portfolio loss than alternative approaches for quantile-based portfolio risk minimization.
Year
DOI
Venue
2008
10.1287/mnsc.1070.0769
Management Science
Keywords
Field
DocType
computationally tractable approximation method,quantile-based portfolio risk minimization,conditional var,accepted risk measure,asymmetry-robust var,efficient optimization,robust value-at-risk optimization,portfolio loss,portfolio var,modified var measure,incorporating asymmetric distributional information,robust optimization technique,value at risk,efficient frontier,coherent risk measure,robust optimization,risk management
Econometrics,Mathematical optimization,Economics,Risk analysis (business),Robust optimization,Project portfolio management,Post-modern portfolio theory,Efficient frontier,Portfolio,Portfolio optimization,Value at risk
Journal
Volume
Issue
ISSN
54
3
0025-1909
Citations 
PageRank 
References 
40
1.98
7
Authors
3
Name
Order
Citations
PageRank
Karthik Natarajan140731.52
Dessislava Pachamanova228017.89
Melvyn Sim31909117.68