Models for heavy-tailed asset returns

Szymon Borak, Adam Misiorek and Rafał Weron
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Szymon Borak: Humboldt-Universität zu Berlin, Center for Applied Statistics and Economics
Adam Misiorek: Santander Consumer Bank S.A.

Chapter 1 in Statistical Tools for Finance and Insurance, 2011, pp 21-55 from Springer

Abstract: Abstract Many of the concepts in theoretical and empirical finance developed over the past decades – including the classical portfolio theory, the Black-Scholes-Merton option pricing model or the RiskMetrics variance-covariance approach to Value at Risk (VaR) – rest upon the assumption that asset returns follow a normal distribution. But this assumption is not justified by empirical data! Rather, the empirical observations exhibit excess kurtosis, more colloquially known as fat tails or heavy tails (Guillaume et al., 1997; Rachev and Mittnik, 2000). The contrast with the Gaussian law can be striking, as in Figure 1.1 where we illustrate this phenomenon using a ten-year history of the Dow Jones Industrial Average (DJIA) index.

Keywords: Stable Distribution; Tail Index; Stable Density; Inverse Gaussian; Hyperbolic Distribution (search for similar items in EconPapers)
Date: 2011
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Related works:
Working Paper: Models for Heavy-tailed Asset Returns (2010)
Working Paper: Models for Heavy-tailed Asset Returns (2010)
Working Paper: Models for heavy-tailed asset returns (2010)
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DOI: 10.1007/978-3-642-18062-0_1

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