Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities?
- 주제(키워드) Bias , HAR model , Long-memory , Realized volatility , Volatility forecasting
- 등재 SCIE, SCOPUS
- 발행기관 Taylor and Francis Inc.
- 발행년도 2018
- URI http://www.dcollection.net/handler/ewha/000000149766
- 본문언어 영어
- Published As http://dx.doi.org/10.1080/03610918.2016.1249882
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
No-constant strategy is considered for the heterogenous autoregressive (HAR) model of Corsi, which is motivated by smaller biases of its estimated HAR coefficients than those of the constant HAR model. The no-constant model produces better forecasts than the constant model for four real datasets of the realized volatilities (RVs) of some major assets. Robustness of forecast improvement is verified for other functions of realized variance and log RV and for the extended datasets of all 20 RVs of Oxford-Man realized library. A Monte Carlo simulation also reveals improved forecasts for some historic HAR model estimated by Corsi. © 2018 Taylor & Francis Group, LLC.
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