Modelling tail risk with tempered stable distributions: an overview

In this study, we investigate the performance of different parametric models with stable and tempered stable distributions for capturing the tail behaviour of log-returns (financial asset returns). First, we define and discuss the properties of stable and tempered stable random variables. We then sh...

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Bibliographic Details
Published in:Annals of operations research Vol. 299; no. 1-2; pp. 1253 - 1280
Main Authors: Fallahgoul, Hasan, Loeper, Gregoire
Format: Journal Article
Language:English
Published: New York Springer US 01.04.2021
Springer
Springer Nature B.V
Subjects:
Analysis
Business and Management
Characteristic functions
Combinatorics
Computer simulation
Distribution
Empirical analysis
Operations research
Operations Research/Decision Theory
Parameter estimation
Performance indices
Random variables
Return on assets
Risk management
S.I.: Recent Developments in Financial Modeling and Risk Management
Theory of Computation
Australia
G12
C5
Lévy process
Tempered stable distribution
Tail risk
Stable distribution
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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Summary:In this study, we investigate the performance of different parametric models with stable and tempered stable distributions for capturing the tail behaviour of log-returns (financial asset returns). First, we define and discuss the properties of stable and tempered stable random variables. We then show how to estimate their parameters and simulate them based on their characteristic functions. Finally, as an illustration, we conduct an empirical analysis to explore the performance of different models representing the distributions of log-returns for the S&P500 and DAX indexes.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03204-3