کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7373833 | 1479770 | 2018 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Are low-frequency data really uninformative? A forecasting combination perspective
ترجمه فارسی عنوان
آیا داده های فرکانس پایین واقعا بی اطلاع هستند؟ چشم انداز ترکیبی پیش بینی
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
چکیده انگلیسی
In this study, we investigate whether low-frequency data improve volatility forecasting when high-frequency data are available. To answer this question, we utilize four forecast combination strategies that combine low-frequency and high-frequency volatility models and employ a rolling window and a range of loss functions in the framework of the novel Model Confidence Set test. Out-of-sample results show that combination forecasts with GARCH-class models can achieve high forecast accuracy. However, the combination forecast methods appear not to significantly outperform individual high-frequency volatility models. Furthermore, we find that models that combine low-frequency and high-frequency volatility yield significantly better performance than other models and combination forecast strategies in both a statistical and economic sense.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: The North American Journal of Economics and Finance - Volume 44, April 2018, Pages 92-108
Journal: The North American Journal of Economics and Finance - Volume 44, April 2018, Pages 92-108
نویسندگان
Feng Ma, Yu Li, Li Liu, Yaojie Zhang,