Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market

Does measurement error matter in volatility forecasting? Empirical evidence from the Chinese stock market
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测量误差在波动率预测中重要吗?

DOI:
10.1016/j.econmod.2019.07.014
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发表时间:
2020-05
期刊:
影响因子:
4.7
通讯作者:
Zhuo Huang
Zhuo Huang
中科院分区:
经济学2区
文献类型:
--
作者:
Yajing Wang;Fang Liang;Tianyi Wang;Zhuo Huang

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基于Bollerslev等人(2016)开发的方法,我们明确考虑了测量误差中的异方差和中国股票价格的高波动性;我们提出了一个新的模型,LogHARQ模型,以适当地预测中国股市的已实现波动率。样本外研究结果表明,LogHARQ模型比现有的对数和线性预测模型表现更好,特别是当实现数量很大时。通过波动性时序的基于效用的经济价值测试也证实了其较好的性能。
Based on methods developed by Bollerslev et al. (2016), we explicitly accounted for the heteroskedasticity in the measurement errors and for the high volatility of Chinese stock prices; we proposed a new model, the LogHARQ model, as a way to appropriately forecast the realized volatility of the Chinese stock market. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. The better performance is also confirmed by the utility based economic value test through volatility timing.
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