کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5091036 1375657 2008 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR
موضوعات مرتبط
علوم انسانی و اجتماعی اقتصاد، اقتصادسنجی و امور مالی اقتصاد و اقتصادسنجی
پیش نمایش صفحه اول مقاله
The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR
چکیده انگلیسی
This paper investigates the role of high-order moments in the estimation of conditional value at risk (VaR). We use the skewed generalized t distribution (SGT) with time-varying parameters to provide an accurate characterization of the tails of the standardized return distribution. We allow the high-order moments of the SGT density to depend on the past information set, and hence relax the conventional assumption in conditional VaR calculation that the distribution of standardized returns is iid. The maximum likelihood estimates show that the time-varying conditional volatility, skewness, tail-thickness, and peakedness parameters of the SGT density are statistically significant. The in-sample and out-of-sample performance results indicate that the conditional SGT-GARCH approach with autoregressive conditional skewness and kurtosis provides very accurate and robust estimates of the actual VaR thresholds.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Banking & Finance - Volume 32, Issue 2, February 2008, Pages 269-282
نویسندگان
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