کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
415683 | 681223 | 2006 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Accurate value-at-risk forecasting based on the normal-GARCH model
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 4, 15 December 2006, Pages 2295–2312
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 4, 15 December 2006, Pages 2295–2312
نویسندگان
Christoph Hartz, Stefan Mittnik, Marc Paolella,