Inference for Heavy-Tailed Data
Applications in Insurance and Finance

Includes detailed theoretical techniques and tools ready to implement for dealing with heavy tailed data in the insurance and finance sectors

Liang Peng (Author), Yongcheng Qi (Author)

9780128046760

Paperback, published 15 August 2017

180 pages
22.9 x 15.1 x 1.3 cm, 0.3 kg

Approx.170 pages

1. Independent Data: bias-corrected estimators, interval estimation, hypothesis tests, choice of sample fraction2. Dependent Data: inference for mixing data, ARMA models, GARCH(1,1) models3. Multivariate Regular Variation: Recent research on hidden regular variation, functional time series.4. Applications: a tool-box in R will be applied to analyse data sets in insurance and finance

Subject Areas: Applied mathematics [PBW], Mathematics [PB]