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Vector error correction heterogeneous autoregressive forecast model of realized volatility and implied volatility

Title
Vector error correction heterogeneous autoregressive forecast model of realized volatility and implied volatility
Authors
Shin J.W.Shin D.W.
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2017
Journal Title
Communications in Statistics: Simulation and Computation
ISSN
0361-0918JCR Link
Citation
pp. 1 - 13
Keywords
CointegrationHAR modelHigh frequency dataLong-memoryVolatility forecasting
Publisher
Taylor and Francis Inc.
Indexed
SCIE; SCOPUS scopus
Abstract
A vector error correction model is proposed for forecasting realized volatility which takes advantage of the cointegration relation between realized volatility and implied volatility. The model is constructed by adding a cointegration error term to a vector-and-unit-root version of the heterogeneous autoregressive (HAR) model of Corsi (2009). The proposed model is easier to implement, extend, and interpret than fractional cointegration models. A Monte Carlo simulation and real data analysis reveal advantages of the proposed model over other existing models of Corsi (2009), Busch Christensen and Nielsen (2011), Cho and Shin (2016), and Bollerslev Patton, and Quaedvlieg (2016). © 2017 Taylor & Francis Group, LLC
DOI
10.1080/03610918.2017.1414250
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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