Ekaterina Morozova EVA Talk Preview
From Anna Munro
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Name: Ekaterina Morozova
Talk Title: Extreme value analysis for mixture models with heavy-tailed impurity
Abstract: While there exists a well-established theory for the asymptotic behaviour of maxima of the i.i.d. sequences, very few results are available for the triangular arrays, when the distribution can change over time. Typically, the papers on this issue deal with convergence to the Gumbel law (see , ) or twice-differentiable distribution .
For practical purposes we describe the procedure of the application of the considered model to the analysis of financial returns. In this context, our research develops the idea that their distribution is somewhere "in between" the exponential and power laws .
 Anderson, C.W., Coles, S.G., and Hüsler, J. (1997). Maxima of Poisson-like variables and related triangular arrays. The Annals of Applied Probability, 7(4), 953–971.
 Chakrabarty, A. and Samorodnitsky, G. (2012). Understanding heavy tails in a bounded world or, is a truncated heavy tail heavy or not? Stochastic models, 28(1), 109–143.
 Dkengne, P.S., Eckert, N., and Naveau, P. (2016). A limiting distribution for maxima of discrete stationary triangular arrays with an application to risk due to avalanches. Extremes, 19(1), 25–40.
 Freitas, A. V. and Hüsler, J. (2003). Condition for the convergence of maxima of random triangular arrays. Extremes, 6(4), 381-394.
 Malevergne, Y., Pisarenko, V. and Sornette, D. (2005). Empirical distributions of stock returns: between the stretched exponential and the power law? Quantitative Finance, 5(4), 379–401.
 Panov, V. and Morozova, E. (2021). Extreme value analysis for mixture models with heavy-tailed impurity. arXiv preprint arXiv:2103.07689.
This talk is a contributed talk at EVA 2021. View the programme here.