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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, Ji Won; Shin, Dong Wan
- Ewha Authors
- 신동완
- SCOPUS Author ID
- 신동완
- Issue Date
- 2019
- Journal Title
- COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
- ISSN
- 0361-0918
1532-4141
- Citation
- COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION vol. 48, no. 5, pp. 1503 - 1515
- Keywords
- Cointegration; HAR model; High frequency data; Long-memory; Volatility forecasting
- Publisher
- TAYLOR &
FRANCIS INC
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- 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).
- DOI
- 10.1080/03610918.2017.1414250
- Appears in Collections:
- 자연과학대학 > 통계학전공 > Journal papers
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