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

被引:6
|
作者
Shin, Ji Won [1 ]
Shin, Dong Wan [1 ]
机构
[1] Ewha Womans Univ, Dept Stat, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Cointegration; HAR model; High frequency data; Long-memory; Volatility forecasting; STATIONARY FRACTIONAL COINTEGRATION; LONG-MEMORY; TIME-SERIES; POWER;
D O I
10.1080/03610918.2017.1414250
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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).
引用
收藏
页码:1503 / 1515
页数:13
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