2016/02/29 by Bernhard Spangl, Sascha Desmettre, Spangl, Bernhard +3
Economics, Econometrics and Finance · Mathematics · #Financial Risk and Volatility Modeling #Statistical Methods and Inference #Statistical Distribution Estimation and Applications
paper · pdf · doi:10.48550/arxiv.1602.08974
We study four different approaches to model time-dependent extremal behavior: dynamics introduced by (a) a state-space model (SSM), (b) a shot-noise-type process with GPD marginals, (c) a copula-based autoregressive model with GPD marginals, and (d) a GLM with GPD marginals (and previous extremal events as regressors). Each of the models is fit against data, and from the fitted data, we simulate corresponding paths according to the respective fitted models. At this simulated data, the respective dependence structure is analyzed in copula plots and judged against its capacity to fit the corresponding inter-arrival distribution.