کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10147150 | 1646440 | 2018 | 58 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Covariance forecasting in equity markets
ترجمه فارسی عنوان
پیش بینی کواریانس در بازارهای سهام
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
چکیده انگلیسی
We compare the performance of popular covariance forecasting models in the context of a portfolio of major European equity indices. We find that models based on high-frequency data offer a clear advantage in terms of statistical accuracy. They also yield more theoretically consistent predictions from an empirical asset pricing perspective, and, lead to superior out-of-sample portfolio performance. Overall, a parsimonious Vector Heterogeneous Autoregressive (VHAR) model that involves lagged daily, weekly and monthly realised covariances achieves the best performance out of the competing models. A promising new simple hybrid covariance estimator is developed that exploits option-implied information and high-frequency data while adjusting for the volatility riskpremium. Relative model performance does not change during the global financial crisis, or, if a different forecast horizon, or, intraday sampling frequency is employed. Finally, our evidence remains robust when we consider an alternative sample of U.S. stocks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Banking & Finance - Volume 96, November 2018, Pages 153-168
Journal: Journal of Banking & Finance - Volume 96, November 2018, Pages 153-168
نویسندگان
Efthymia Symitsi, Lazaros Symeonidis, Apostolos Kourtis, Raphael Markellos,