Predicting the Tail Behavior of Financial Times Stock Exchange/Johannesburg Stock Exchange (FTSE/JSE) Closing Banking Indices: Extreme Value Theory Approach

DOI10.1007/978-3-030-54108-8_2OpenAlexW3131921017MaRDI QIDQ5049418

Ntebo Moroke, Elias Munapo, Katleho Makatjane

Publication date: 11 November 2022

Published in: Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-54108-8_2

zbMATH Keywords

maximum likelihood estimationextreme value theorygeneralized Pareto distributionvolatility clusteringgeneralized extreme valuefat-tail\(\mathrm{MS(2)}\)-\(\mathrm{EGARCH}(p,q)\)block minima methodindependently and identically distributed

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05)

Uses Software

• ismev
• QRM

Cites Work

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• Conditional tail expectation of randomly weighted sums with heavy-tailed distributions
• Fitting the generalized Pareto distribution to data using maximum goodness-of-fit estimators
• Generalized autoregressive conditional heteroscedasticity
• On the block maxima method in extreme value theory: PWM estimators
• Existence and consistency of the maximum likelihood estimators for the extreme value index within the block maxima framework
• Robust and efficient estimation for the generalized Pareto distribution
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Parameter and Quantile Estimation for the Generalized Pareto Distribution
• Goodness of fit for the extreme value distribution
• An introduction to statistical modeling of extreme values

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