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Stability analysis of portfolio management with conditional value-at-risk

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Stability analysis of portfolio management with conditional value-at-risk. / Kaut, Michal; Vladimirou, Hercules; Wallace, Stein W et al.
In: Quantitative Finance, Vol. 7, No. 4, 2007, p. 397-409.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Kaut, M, Vladimirou, H, Wallace, SW & Zenios, S 2007, 'Stability analysis of portfolio management with conditional value-at-risk', Quantitative Finance, vol. 7, no. 4, pp. 397-409. https://doi.org/10.1080/14697680701483222

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Vancouver

Kaut M, Vladimirou H, Wallace SW, Zenios S. Stability analysis of portfolio management with conditional value-at-risk. Quantitative Finance. 2007;7(4):397-409. doi: 10.1080/14697680701483222

Author

Kaut, Michal ; Vladimirou, Hercules ; Wallace, Stein W et al. / Stability analysis of portfolio management with conditional value-at-risk. In: Quantitative Finance. 2007 ; Vol. 7, No. 4. pp. 397-409.

Bibtex

@article{8c11c72f04284fb695b526587c8b9134,
title = "Stability analysis of portfolio management with conditional value-at-risk",
abstract = "We examine the stability of a portfolio management model based on the conditional value-at-risk (CVaR) measure; the model controls risk exposure of international investment portfolios. We use a moment-matching method to generate discrete distributions (scenario sets) of asset returns and exchange rates so that their statistical properties match corresponding values estimated from historical data. First, we establish that the scenario generation procedure does not bias the results of the optimization program, and we determine the required number of scenarios to attain stable solutions. We then investigate the sensitivity of the CVaR model to mis-specifications in the statistics of stochastic parameters: mean, standard deviation, skewness, kurtosis, as well as correlations. The results are most sensitive to estimation errors in the means of the stochastic parameters (asset returns and currency exchange rates). Mis-specifications in the standard deviation, skewness and correlations of the random parameters also have considerable impact on the solutions. The effect of mis-specifications in the values of kurtosis, although less than that of the other statistics, is still not negligible.",
keywords = "Portfolio management, Stability analysis , Impact of higher-order moments , Estimation errors , Conditional value-at-risk",
author = "Michal Kaut and Hercules Vladimirou and Wallace, {Stein W} and Stavros Zenios",
year = "2007",
doi = "10.1080/14697680701483222",
language = "English",
volume = "7",
pages = "397--409",
journal = "Quantitative Finance",
issn = "1469-7688",
publisher = "Routledge",
number = "4",

}

RIS

TY - JOUR

T1 - Stability analysis of portfolio management with conditional value-at-risk

AU - Kaut, Michal

AU - Vladimirou, Hercules

AU - Wallace, Stein W

AU - Zenios, Stavros

PY - 2007

Y1 - 2007

N2 - We examine the stability of a portfolio management model based on the conditional value-at-risk (CVaR) measure; the model controls risk exposure of international investment portfolios. We use a moment-matching method to generate discrete distributions (scenario sets) of asset returns and exchange rates so that their statistical properties match corresponding values estimated from historical data. First, we establish that the scenario generation procedure does not bias the results of the optimization program, and we determine the required number of scenarios to attain stable solutions. We then investigate the sensitivity of the CVaR model to mis-specifications in the statistics of stochastic parameters: mean, standard deviation, skewness, kurtosis, as well as correlations. The results are most sensitive to estimation errors in the means of the stochastic parameters (asset returns and currency exchange rates). Mis-specifications in the standard deviation, skewness and correlations of the random parameters also have considerable impact on the solutions. The effect of mis-specifications in the values of kurtosis, although less than that of the other statistics, is still not negligible.

AB - We examine the stability of a portfolio management model based on the conditional value-at-risk (CVaR) measure; the model controls risk exposure of international investment portfolios. We use a moment-matching method to generate discrete distributions (scenario sets) of asset returns and exchange rates so that their statistical properties match corresponding values estimated from historical data. First, we establish that the scenario generation procedure does not bias the results of the optimization program, and we determine the required number of scenarios to attain stable solutions. We then investigate the sensitivity of the CVaR model to mis-specifications in the statistics of stochastic parameters: mean, standard deviation, skewness, kurtosis, as well as correlations. The results are most sensitive to estimation errors in the means of the stochastic parameters (asset returns and currency exchange rates). Mis-specifications in the standard deviation, skewness and correlations of the random parameters also have considerable impact on the solutions. The effect of mis-specifications in the values of kurtosis, although less than that of the other statistics, is still not negligible.

KW - Portfolio management

KW - Stability analysis

KW - Impact of higher-order moments

KW - Estimation errors

KW - Conditional value-at-risk

U2 - 10.1080/14697680701483222

DO - 10.1080/14697680701483222

M3 - Journal article

VL - 7

SP - 397

EP - 409

JO - Quantitative Finance

JF - Quantitative Finance

SN - 1469-7688

IS - 4

ER -