Stable modeling of value at risk

I. Khindanova; S. Rachev; E. Schwartz

doi:10.1016/S0895-7177(01)00129-7

Stable modeling of value at risk

I. Khindanova, S. Rachev, E. Schwartz

Mathematics and Statistics

Research output: Contribution to journal › Article › peer-review

30 Scopus citations

Abstract

The value-at-risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible losses. In this paper, we analyze the use of stable Paretian distributions in VAR modeling.

Original language	English
Pages (from-to)	1223-1259
Number of pages	37
Journal	Mathematical and Computer Modelling
Volume	34
Issue number	9-11
DOIs	https://doi.org/10.1016/S0895-7177(01)00129-7
State	Published - Sep 24 2001

Keywords

Market risks
Stable Paretian distributions
VAR computations
Value-at-risk

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10.1016/S0895-7177(01)00129-7

Cite this

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abstract = "The value-at-risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible losses. In this paper, we analyze the use of stable Paretian distributions in VAR modeling.",

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AU - Rachev, S.

AU - Schwartz, E.

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N2 - The value-at-risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible losses. In this paper, we analyze the use of stable Paretian distributions in VAR modeling.

AB - The value-at-risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations - the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing - do not provide satisfactory evaluation of possible losses. In this paper, we analyze the use of stable Paretian distributions in VAR modeling.

KW - Market risks

KW - Stable Paretian distributions

KW - VAR computations

KW - Value-at-risk

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JO - Mathematical and Computer Modelling

JF - Mathematical and Computer Modelling

IS - 9-11

ER -

Stable modeling of value at risk

Abstract

Keywords

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