Stable Paretian Models in Finance

By Svetlozar T. Rachev, Stefan Mittnik. 2000

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Citations in the corpus

Parameter Estimation for the Truncated Pareto Distribution (2006, background): “…and Mikosch 1997; Fama 1965; Jansen and de Vries 1991; Loretan and Phillips 1994; Mandelbrot 1963; McCulloch 1996; Meerschaert and Scheffler 2003; Rachev and Mittnik 2000), physics (Barkai, Metzler, and Klafter 2000; Klafter, Blumen, and Shlesinger 1987; Kotulski 1995; Meerschaert, Benson,…”
Momentum strategies based on reward-risk stock selection criteria (2007, background): “Since this initial work in the 1960s, the stable distribution has been applied to modeling both the unconditional and conditional return distributions, as well as providing a theoretical framework of portfolio theory and market equilibrium models (Rachev and Mittnik, 2000).”
Models for Heavy-tailed Asset Returns (2010, background): “Mandelbrot’s (1963) seminal work on applying stable distributions in finance gained support in the first few years after its publication, but subsequent works have questioned the stable distribution hypothesis, in particular, the stability under summation (for a review see Rachev and Mittnik, 2000).”
Multivariate Skewed Student's t Copula in the Analysis of Nonlinear and Asymmetric Dependence in the German Equity Market (2008, methodology): “…of these processes have been discussed in Mandelbrot and van Ness (1968), Maejima (1983), Maejima and Rachev (1987), Manfields et al. (2001), Rachev and Mittnik (2000), Rachev and Samorodnitsky (2001), Samorodnitsky (1994), Samorodinitsky and Taqqu (1994), and Cohen and Samorodnitsky…”
An Introduction to Univariate GARCH Models (2006, background): “Rachev and Mittnik (2000) contains an informative discussion of stable Paretian distributions and their use in nance and econometrics.”
Portfolio diversification and value at risk under thick-tailedness (2009, unknown): “…models and statistical techniques, subsequent research reported the following estimates of the tail parameters for returns on various stocks and stock indices: 35 55 (Jansen and de Vries 1991); 25 54 (Loretan and Phillips 1994); 1.55 52 (McCulloch 1996, 1997); 0.95 52 (Rachev and Mittnik 2000).”
Goodness-of-fit tests for symmetric stable distributions—Empirical characteristic function approach (2006, background): “Concerning statistical inference, because of their attractive properties such as heavy tails, many models based on stable distributions have been considered in both social and natural sciences (Samorodnitsky and Taqqu (1994), Uchaikin and Zolotarev (1999), Rachev and Mittnik (2000)).”
Modeling Movie Success When ‘Nobody Knows Anything’: Conditional Stable-Distribution Analysis Of Film Returns (2005, background): “est in the stable distribution in finance, including applications to modeling asset returns, foreign exchange rates, interest rate and commodity price movements, and real estate returns ( Rachev and Mittnik, 2000; McCulloch, 1996).”
Interval estimation of value-at-risk based on GARCH models with heavy-tailed innovations (2007, methodology): “As pointed out by Rachev and Mittnik (2000), one weakness of the VaR methodology comes from model (mis-)specification risk.”
Potential Theory of Geometric Stable Processes (2006, background): “Since the function φ is a complete Bernstein function, the Lévy measure µ has a complete monotone density µ(t).”