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

Yajing Wang, Fang Liang, Tianyi Wang () and Zhuo Huang

Economic Modelling, 2020, vol. 87, issue C, 148-157

Abstract: 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.

Keywords: Realized volatility; Measurement errors; Volatility forecasting; Chinese stock market (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 C58 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:87:y:2020:i:c:p:148-157

DOI: 10.1016/j.econmod.2019.07.014

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