50 Years of Journal of Applied Statistics: Extreme Value Theory and its Applications in Finance, Edited by Michael Grabchak
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The fiftieth birthday of the Journal of Applied Statistics is a good occasion to look back on the various trends in applied statistics over the past half century. Here, we focus on the rise in prominence of financial applications, which brought with it a renewed focus on extreme values and heavy tails. In this article collection we present a cross section of articles from JAS that lie at the intersection of extreme value theory and finance. These range from what is likely the earliest article that JAS published on this topic more than 20 years ago, to recent work published just this year. The underlying statistics runs the gamut from parameter estimation and confidence intervals to goodness-of-fit testing, Bayesian methods, change point analysis, and copulas. Applications include risk estimation, hedging strategies, and the modelling of loan defaults, among others. While not every article in this collection deals directly with financial applications or extreme value theory, we feel that all would be of interest to researchers in either or both of these areas.
Edited by Michael Grabchak, Department of Mathematics and Statistics, University of North Carolina Charlotte