Please use this identifier to cite or link to this item:
|Title:||Incorporating asymmetric distributional information in robust value-at-risk optimization|
|Authors:||Natarajan, K. |
|Keywords:||Coherent risk measures|
|Citation:||Natarajan, K., Pachamanova, D., Sim, M. (2008). Incorporating asymmetric distributional information in robust value-at-risk optimization. Management Science 54 (3) : 573-585. ScholarBank@NUS Repository. https://doi.org/10.1287/mnsc.1070.0769|
|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. © 2008 INFORMS.|
|Source Title:||Management Science|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Aug 7, 2018
WEB OF SCIENCETM
checked on Jul 23, 2018
checked on Jun 30, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.