Generalized Pareto processes and fund liquidity risk
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Publication:4554499
DOI10.1080/14697688.2017.1410214zbMATH Open1400.91658arXiv1702.06993OpenAlexW2793357235MaRDI QIDQ4554499
Author name not available (Why is that?)
Publication date: 14 November 2018
Published in: (Search for Journal in Brave)
Abstract: Motivated by the modeling of liquidity risk in fund management in a dynamic setting, we propose and investigate a class of time series models with generalized Pareto marginals: the autoregressive generalized Pareto process (ARGP), a modified ARGP (MARGP) and a thresholded ARGP (TARGP). These models are able to capture key data features apparent in fund liquidity data and reflect the underlying phenomena via easily interpreted, low-dimensional model parameters. We establish stationarity and ergodicity, provide a link to the class of shot-noise processes, and determine the associated interarrival distributions for exceedances. Moreover, we provide estimators for all relevant model parameters and establish consistency and asymptotic normality for all estimators (except the threshold parameter, which as usual must be dealt with separately). Finally, we illustrate our approach using real-world fund redemption data, and we discuss the goodness-of-fit of the estimated models.
Full work available at URL: https://arxiv.org/abs/1702.06993
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