The Improved Value-at-Risk for Heteroscedastic Processes and Their Coverage Probability

المؤلف

Syuhada, Khreshna

المصدر

Journal of Probability and Statistics

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-5، 5ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-03-10

دولة النشر

مصر

عدد الصفحات

5

التخصصات الرئيسية

الرياضيات

الملخص EN

A risk measure commonly used in financial risk management, namely, Value-at-Risk (VaR), is studied.

In particular, we find a VaR forecast for heteroscedastic processes such that its (conditional) coverage probability is close to the nominal.

To do so, we pay attention to the effect of estimator variability such as asymptotic bias and mean square error.

Numerical analysis is carried out to illustrate this calculation for the Autoregressive Conditional Heteroscedastic (ARCH) model, an observable volatility type model.

In comparison, we find VaR for the latent volatility model i.e., the Stochastic Volatility Autoregressive (SVAR) model.

It is found that the effect of estimator variability is significant to obtain VaR forecast with better coverage.

In addition, we may only be able to assess unconditional coverage probability for VaR forecast of the SVAR model.

This is due to the fact that the volatility process of the model is unobservable.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Syuhada, Khreshna. 2020. The Improved Value-at-Risk for Heteroscedastic Processes and Their Coverage Probability. Journal of Probability and Statistics،Vol. 2020, no. 2020, pp.1-5.
https://search.emarefa.net/detail/BIM-1190184

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Syuhada, Khreshna. The Improved Value-at-Risk for Heteroscedastic Processes and Their Coverage Probability. Journal of Probability and Statistics No. 2020 (2020), pp.1-5.
https://search.emarefa.net/detail/BIM-1190184

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Syuhada, Khreshna. The Improved Value-at-Risk for Heteroscedastic Processes and Their Coverage Probability. Journal of Probability and Statistics. 2020. Vol. 2020, no. 2020, pp.1-5.
https://search.emarefa.net/detail/BIM-1190184

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1190184