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A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models

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A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models. / Mukherjee, Kanchan; Iqbal, Farhat.
In: Journal of Forecasting, Vol. 31, No. 5, 08.2012, p. 377-390.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Mukherjee, K & Iqbal, F 2012, 'A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models', Journal of Forecasting, vol. 31, no. 5, pp. 377-390. https://doi.org/10.1002/for.1224

APA

Mukherjee, K., & Iqbal, F. (2012). A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models. Journal of Forecasting, 31(5), 377-390. https://doi.org/10.1002/for.1224

Vancouver

Mukherjee K, Iqbal F. A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models. Journal of Forecasting. 2012 Aug;31(5):377-390. Epub 2011 Feb 26. doi: 10.1002/for.1224

Author

Mukherjee, Kanchan ; Iqbal, Farhat. / A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models. In: Journal of Forecasting. 2012 ; Vol. 31, No. 5. pp. 377-390.

Bibtex

@article{dbaeb8dd0ab548ff845ca526b678ba88,
title = "A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models",
abstract = "In this paper, we investigate the performance of a class of M-estimators for bothsymmetric and asymmetric conditional heteroscedastic models in the predictionof value-at-risk. The class of estimators includes the least absolute deviation(LAD), Huber{\textquoteright}s, Cauchy and B-estimator, as well as the well-known quasimaximum likelihood estimator (QMLE). We use a wide range of summarystatistics to compare both the in-sample and out-of-sample VaR estimates ofthree well-known stock indices. Our empirical study suggests that in generalCauchy, Huber and B-estimator have better performance in predicting one-step ahead VaR than the commonly used QMLE.",
keywords = "value-at-risk, GARCH , GJR , M-estimators , M-tests for financial data",
author = "Kanchan Mukherjee and Farhat Iqbal",
year = "2012",
month = aug,
doi = "10.1002/for.1224",
language = "English",
volume = "31",
pages = "377--390",
journal = "Journal of Forecasting",
issn = "0277-6693",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

RIS

TY - JOUR

T1 - A study of Value-at-Risk based on M-estimators of the conditional heteroscedastic models

AU - Mukherjee, Kanchan

AU - Iqbal, Farhat

PY - 2012/8

Y1 - 2012/8

N2 - In this paper, we investigate the performance of a class of M-estimators for bothsymmetric and asymmetric conditional heteroscedastic models in the predictionof value-at-risk. The class of estimators includes the least absolute deviation(LAD), Huber’s, Cauchy and B-estimator, as well as the well-known quasimaximum likelihood estimator (QMLE). We use a wide range of summarystatistics to compare both the in-sample and out-of-sample VaR estimates ofthree well-known stock indices. Our empirical study suggests that in generalCauchy, Huber and B-estimator have better performance in predicting one-step ahead VaR than the commonly used QMLE.

AB - In this paper, we investigate the performance of a class of M-estimators for bothsymmetric and asymmetric conditional heteroscedastic models in the predictionof value-at-risk. The class of estimators includes the least absolute deviation(LAD), Huber’s, Cauchy and B-estimator, as well as the well-known quasimaximum likelihood estimator (QMLE). We use a wide range of summarystatistics to compare both the in-sample and out-of-sample VaR estimates ofthree well-known stock indices. Our empirical study suggests that in generalCauchy, Huber and B-estimator have better performance in predicting one-step ahead VaR than the commonly used QMLE.

KW - value-at-risk

KW - GARCH

KW - GJR

KW - M-estimators

KW - M-tests for financial data

U2 - 10.1002/for.1224

DO - 10.1002/for.1224

M3 - Journal article

VL - 31

SP - 377

EP - 390

JO - Journal of Forecasting

JF - Journal of Forecasting

SN - 0277-6693

IS - 5

ER -