Evaluating the RiskMetrics methodology in measuring volatility and Value-at-Risk in financial markets

Szilárd Pafka and Imre Kondor ()

Physica A: Statistical Mechanics and its Applications, 2001, vol. 299, issue 1, 305-310

Abstract: We analyze the performance of RiskMetrics, a widely used methodology for measuring market risk. Based on the assumption of normally distributed returns, the RiskMetrics model completely ignores the presence of fat tails in the distribution function, which is an important feature of financial data. Nevertheless, it was commonly found that RiskMetrics performs satisfactorily well, and therefore the technique has become widely used in the financial industry. We find, however, that the success of RiskMetrics is the artifact of the choice of the risk measure. First, the outstanding performance of volatility estimates is basically due to the choice of a very short (one-period ahead) forecasting horizon. Second, the satisfactory performance in obtaining Value-at-Risk by simply multiplying volatility with a constant factor is mainly due to the choice of the particular significance level.

Keywords: RiskMetrics; Market risk; Risk measurement; Volatility; Value-at-Risk (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (18)

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Working Paper: Evaluating the RiskMetrics Methodology in Measuring Volatility and Value-at-Risk in Financial Markets (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:299:y:2001:i:1:p:305-310

DOI: 10.1016/S0378-4371(01)00310-7

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