Impact of overnight information on MEM volatility prediction
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AbstractOvernight return in stock market is one kind of information that can reflect the volatility of the corresponding financial instrument. However, some volatility estimators, either based on range-based or high-frequency data, do not include this information in their formulations. In this study, we investigate the impact of overnight return on Engle's Multiplicative Error Model (MEM). Garman's and Hansen's whole-day-based estimators are studied to demonstrate the effects under minimum-variance situations. Besides, a general framework for incorporating overnight information is proposed and the results are discussed. Our findings demonstrate that overnight return gives a non-monotonic influence and it does contain useful information for predicting the CBOE volatility indexes under specific combinations.
All Author(s) ListChu CF, Lam KP
Journal nameStatistics and Its Interface
Volume Number1
Issue Number2
Pages297 - 306
LanguagesEnglish-United Kingdom
KeywordsMEM; Multiplicative Error Model; Overnight return; Volatility forecast
Web of Science Subject CategoriesMathematical & Computational Biology; MATHEMATICAL & COMPUTATIONAL BIOLOGY; Mathematics; Mathematics, Interdisciplinary Applications; MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Last updated on 2020-11-08 at 03:02