Model risk in portfolio optimization
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Author / Producer
Date
2014
Publication Type
Journal Article
ETH Bibliography
yes
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Abstract
We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.
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Publication status
published
External links
Editor
Book title
Journal / series
Volume
2 (3)
Pages / Article No.
315 - 348
Publisher
MDPI
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Portfolio optimization; Asset allocation; Model risk; Estimation uncertainty; Covariance estimation
Organisational unit
08813 - Wüthrich, Mario Valentin (Tit.-Prof.)