Extreme value theory as a risk management tool
P Embrechts, SI Resnick… - North American Actuarial …, 1999 - Taylor & Francis
The financial industry, including banking and insurance, is undergoing major changes. The
(re) insurance industry is increasingly exposed to catastrophic losses for which the …
(re) insurance industry is increasingly exposed to catastrophic losses for which the …
Backtesting expected shortfall: accounting for tail risk
The Basel Committee on Banking Supervision (BIS) has recently sanctioned expected
shortfall (ES) as the market risk measure to be used for banking regulatory purposes …
shortfall (ES) as the market risk measure to be used for banking regulatory purposes …
[BOOK][B] Extreme values in finance, telecommunications, and the environment
B Finkenstadt, H Rootzén - 2003 - books.google.com
Because of its potential to... predict the unpredictable,... extreme value theory (EVT) and
methodology is currently receiving a great deal of attention from statistical and mathematical …
methodology is currently receiving a great deal of attention from statistical and mathematical …
Evaluating value-at-risk models via quantile regression
This article is concerned with evaluating Value-at-Risk estimates. It is well known that using
only binary variables, such as whether or not there was an exception, sacrifices too much …
only binary variables, such as whether or not there was an exception, sacrifices too much …
Tail risk dynamics in stock returns: Links to the macroeconomy and global markets connectedness
D Massacci - Management Science, 2017 - pubsonline.informs.org
We propose a new time-varying peaks over threshold model to study tail risk dynamics in
equity markets: the laws of motion for the parameters are defined through the score-based …
equity markets: the laws of motion for the parameters are defined through the score-based …
Modeling dependence and tails of financial time series
T Mikosch - Monographs on Statistics and Applied Probability, 2004 - api.taylorfrancis.com
Contents 5.1 “Stylized facts” about financial data................................... 1875.1. 1 Distribution
and tails.......................................... 188 5.1. 2 Dependence, autocorrelations, and clusters of …
and tails.......................................... 188 5.1. 2 Dependence, autocorrelations, and clusters of …
Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory
We propose nonparametric estimators for conditional value-at-risk (CVaR) and conditional
expected shortfall (CES) associated with conditional distributions of a series of returns on a …
expected shortfall (CES) associated with conditional distributions of a series of returns on a …
Revisiting the accuracy of standard VaR methods for risk assessment: using the copula–EVT multidimensional approach for stock markets in the MENA region
A Chebbi, A Hedhli - The Quarterly Review of Economics and Finance, 2022 - Elsevier
The aim of this study is twofold. First, it aims to show how to overcome some of the
shortcomings of the standard risk measurement methods using value-at-risk (VaR) in the …
shortcomings of the standard risk measurement methods using value-at-risk (VaR) in the …
Asymptotics for GARCH squared residual correlations
We develop an asymptotic theory for quadratic forms of the autocorrelations of squared
residuals from a GARCH (p, q) model. Denoting by, k≥ 1, these autocorrelations computed …
residuals from a GARCH (p, q) model. Denoting by, k≥ 1, these autocorrelations computed …
Backtesting VaR and expectiles with realized scores
Several statistical functionals such as quantiles and expectiles arise naturally as the
minimizers of the expected value of a scoring function, a property that is called elicitability …
minimizers of the expected value of a scoring function, a property that is called elicitability …