Estimation Error Of Expected Shortfall

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Estimation Error Of Expected Shortfall

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Author : Imre Kondor
language : en
Publisher:
Release Date : 2014

Estimation Error Of Expected Shortfall written by Imre Kondor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.

The problem of estimation error of Expected Shortfall is analyzed, with a view of its introduction as a global regulatory risk measure.

Contour Map Of Estimation Error For Expected Shortfall

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Author : Imre Kondor
language : en
Publisher:
Release Date : 2015

Contour Map Of Estimation Error For Expected Shortfall written by Imre Kondor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

The contour map of estimation error of Expected Shortfall (ES) is constructed. It allows one to quantitatively determine the sample size (the length of the time series) required by the optimization under ES of large institutional portfolios for a given size of the portfolio, at a given confidence level and a given estimation error.

On The Role Of The Estimation Error In Prediction Of Expected Shortfall

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Author : Carl Lönnbark
language : en
Publisher:
Release Date : 2012

On The Role Of The Estimation Error In Prediction Of Expected Shortfall written by Carl Lönnbark and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

Comparative Analyses Of Expected Shortfall And Var

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Author : Yasuhiro Yamai
language : en
Publisher:
Release Date : 2001

Comparative Analyses Of Expected Shortfall And Var written by Yasuhiro Yamai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Financial futures categories.

Expected shortfall is compared with Value-at-Risk (VaR) in three aspects: estimation errors, decomposition into risk factors, and optimization. Advantages and disadvantages of expected shortfall over VaR are shown, and that expected shortfall is easily decomposed (needing a larger size of sample than VaR for the same level of accuracy) and optimized, while VaR is not.

Portfolio Optimization Under Expected Shortfall

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Author :
language : en
Publisher:
Release Date : 2015

Portfolio Optimization Under Expected Shortfall written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

Backtesting Value At Risk And Expected Shortfall In The Presence Of Estimation Error

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Author : Sander Barendse
language : en
Publisher:
Release Date : 2019

Backtesting Value At Risk And Expected Shortfall In The Presence Of Estimation Error written by Sander Barendse and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

We investigate the effect of estimation error on backtests of (multi-period) expected shortfall (ES) forecasts. These backtests are based on first order conditions of a recently introduced family of jointly consistent loss functions for Value-at-Risk (VaR) and ES. We provide explicit expressions for the additional terms in the asymptotic covariance matrix that result from estimation error, and propose robust tests that account for it. Monte Carlo experiments show that the tests that ignore these terms suffer from size distortions, which are more pronounced for higher ratios of outof-sample to in-sample observations. Robust versions of the backtests perform well, although this also depends on the choice of conditioning variables. In an application to VaR and ES forecasts for daily FTSE 100 index returns as generated by AR-GARCH, AR-GJR-GARCH, and AR-HEAVY models, we find that estimation error substantially impacts the outcome of the backtests.

Estimation Risk In Financial Risk Management

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Author : Daniel Giamouridis
language : en
Publisher:
Release Date : 2008

Estimation Risk In Financial Risk Management written by Daniel Giamouridis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

Christoffersen and Goncalves (2005) study the effect of parameter estimation error in computing Value at Risk and Expected Shortfall through commonly used methods including the Cornish-Fisher/Gram-Charlier approximations approach. We provide a correction to the expression used for the computation of the Expected Shortfall under the Cornish-Fisher/Gram-Charlier approximations and illustrate the effect of the error found in assessing the accuracy of Expected Shortfall point forecasts.

Nonparametric Estimation Of Expected Shortfall

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Author : Song Xi Chen
language : en
Publisher:
Release Date : 2010

Nonparametric Estimation Of Expected Shortfall written by Song Xi Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

The expected shortfall is an increasingly popular risk measure in financial risk management and it possesses the desired sub-additivity property, which is lacking for the value at risk (VaR). We consider two nonparametric expected shortfall estimators for dependent financial losses. One is a sample average of excessive losses larger than a VaR. The other is a kernel smoothed version of the first estimator (Scaillet, 2004 Mathematical Finance), hoping that more accurate estimation can be achieved by smoothing. Our analysis reveals that the extra kernel smoothing does not produce more accurate estimation of the shortfall. This is different from the estimation of the VaR where smoothing has been shown to produce reduction in both the variance and the mean square error of estimation. Therefore, the simpler ES estimator based on the sample average of excessive losses is attractive for the shortfall estimation.

Nonparametric Versus Parametric Expected Shortfall

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Author : Doug Martin
language : en
Publisher:
Release Date : 2019

Nonparametric Versus Parametric Expected Shortfall written by Doug Martin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

We use influence functions as a basic tool to study unconditional non-parametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence. Non-parametric ES estimators have a monotonically decreasing influence function of returns. ES maximum-likelihood estimator (MLE) influence functions are non-monotonic and approximately symmetric, resulting in large positive returns contributing to risk. However, ES MLE's have the lowest possible asymptotic variance among consistent ES estimators. Influence functions are used to derive large sample standard error formulas for both types of ES estimators for normal and t-distributions and evaluate non-parametric ES estimator inefficiency. Monte Carlo results determine finite-sample sizes for which the standard errors of which both types of ES estimators are sufficiently accurate to be used in practice. Non-monotonicity of ES MLE's led us to study modification of normal distribution MLE's in which standard deviation is replaced by semi-standard deviation (SSD). Influence function theory is used to establish a condition under which an SSD based ES risk estimator has a monotonic influence functions and the underlying risk measures is coherent. It is also shown that the SSD based estimator's asymptotic standard error is only slightly larger than that of the standard deviation-based estimator.

Backtesting Value At Risk And Expected Shortfall

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Author : Simona Roccioletti
language : en
Publisher: Springer
Release Date : 2015-12-04

Backtesting Value At Risk And Expected Shortfall written by Simona Roccioletti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-04 with Business & Economics categories.

In this book Simona Roccioletti reviews several valuable studies about risk measures and their properties; in particular she studies the new (and heavily discussed) property of "Elicitability" of a risk measure. More important, she investigates the issue related to the backtesting of Expected Shortfall. The main contribution of the work is the application of "Test 1" and "Test 2" developed by Acerbi and Szekely (2014) on different models and for five global market indexes.