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Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities?

Title
Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities?
Authors
Song H.Shin D.W.Yoo J.K.
Ewha Authors
신동완유재근
SCOPUS Author ID
신동완scopus; 유재근scopus
Issue Date
2018
Journal Title
Communications in Statistics: Simulation and Computation
ISSN
0361-0918JCR Link
Citation
vol. 47, no. 1, pp. 63 - 73
Keywords
BiasHAR modelLong-memoryRealized volatilityVolatility forecasting
Publisher
Taylor and Francis Inc.
Indexed
SCIE; SCOPUS scopus
Abstract
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.
DOI
10.1080/03610918.2016.1249882
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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