Portfolio Optimization under VaR Constraints Based on Dynamic Estimates of the Variance-Covariance Matrix

Katja Specht () and Peter Winker
Additional contact information
Katja Specht: Pforzheim University of Applied Sciences

A chapter in Computational Methods in Financial Engineering, 2008, pp 73-94 from Springer

Abstract: Abstract The concept of Value at Risk (VaR) is eminently intuitive and easy to interpret. However, there are two major problems in its practical application: reliable estimations are difficult to perform and using the VaR as a constraint in portfolio optimization causes computational problems. Both problems are taken into account in the present application. First, the VaR based on estimates of the conditional covariance matrix with the ”Principal Components GARCH model” (PC GARCH model) is calculated. Second, recent advances in heuristic optimization (a modified version of Memetic Algorithms) are applied in order to deal with the computational problems. The computational study indicates that the proposed method for estimating the conditional covariance matrix, the PC GARCH model, results in much better approximations of the conditional volatility structure than a simple historical estimate. This advantage in modelling is exploited by the optimization algorithm to identify portfolios with higher expected return given a fixed VaR constraint. However, adjusting the portfolio to the dynamic approximations of the conditional volatility structure also results in some overconfidence with regard to the risk constraint.

Keywords: Portfolio optimization; value at risk; heuristic optimization; memetic algorithms; dynamic variance-covariance matrix (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-77958-2_4

Ordering information: This item can be ordered from
http://www.springer.com/9783540779582

DOI: 10.1007/978-3-540-77958-2_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().