Value at Risk Calculations, Extreme Events, and Tail Estimation

Neftçi, Salih N.

doi:10.3905/jod.2000.319126

Cited by 166 publications

(94 citation statements)

References 3 publications

(3 reference statements)

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“…Recently, numerous research studies have analyzed the extreme variations that financial markets are subject to, mostly because of currency crises, stock market crashes and large credit defaults. The tail behaviour of financial series has, among others, been discussed in Koedijk et al (1990), Dacorogna et al (1995), Loretan and Phillips (1994), Longin (1996), Danielsson and de Vries (2000), Kuan and Webber (1998), Straetmans (1998), McNeil (1999), Jondeau and Rockinger (1999), Rootzèn and Klüppelberg (1999), Neftci (2000), McNeil and Frey (2000) and Gençay et al (2003b). An interesting discussion about the potential of extreme value theory in risk management is given in Diebold et al (1998).…”

Section: Introductionmentioning

confidence: 99%

An Application of Extreme Value Theory for Measuring Financial Risk

Gilli

Këllezi²

2006

Comput Econ

312

230

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Assessing the probability of rare and extreme events is an important issue in the risk management of financial portfolios. Extreme value theory provides the solid fundamentals needed for the statistical modelling of such events and the computation of extreme risk measures. The focus of the paper is on the use of extreme value theory to compute tail risk measures and the related confidence intervals, applying it to several major stock market indices.

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Section: Introductionmentioning

confidence: 99%

An Application of Extreme Value Theory for Measuring Financial Risk

Gilli

Këllezi²

2006

Comput Econ

312

230

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“…Section VI runs a battery of robustness checks. Section VII compares the relative performance of realized variance and VaR in 'Longin (2000), Neftci (2000), and Bali (2003) find that VaR provides good predictions of catastrophic market risks and performs surprisingly well in capturing both the rate of occurrence and the extent of extreme events in financial markets. However, the traditional measures of market risk such as conditional variance and standard deviation yield an inaccurate characterization of extreme movements in financial markets.…”

mentioning

confidence: 99%

Is There an Intertemporal Relation between Downside Risk and Expected Returns?

Bali¹,

Demirtaş²,

Levy³

2009

J. Financ. Quant. Anal.

265

146

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This paper examines the intertemporal relation between downside risk and expected stock returns. Value at Risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared with the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).

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“…Marshall and Sigel found that failures of risk management have led to a widespread call improved quantification of financial risk (Marshall & Sigel, 1997). The problem of applying VaR in practice was evident because empirical returns distributions tend to have tails that look quite different from those of the normal and lognormal distributions that we typically assume in finance (Neftchi, 2000).…”

Section: Literature Reviewmentioning

confidence: 99%