Intraday volatility analysis of CSI 300 index futures: a dependent functional data method

Danni Wang, Zhifang Su and Qifang Li

Economic Research-Ekonomska Istraživanja, 2023, vol. 36, issue 1, 312-332

Abstract: This study introduces a new volatility model based on dependent functional data to investigate the intraday volatility characteristics of CSI 300 in the context of high-frequency data. The volatility curve is fitted and reconstructed using three methods: functional principal component analysis, Newey-West kernel, and truncation-free Bartlett kernel. We adopt a functional time series approach for short-term dynamic forecasting. The empirical results show that the proposed dependent functional volatility estimation model based on the long-term covariance of the truncated Bartlett kernel can accurately capture the intraday volatility trajectory and outperforms other models in terms of forecast accuracy and profitability. This study improves the volatility-related research methodology, which is conducive to discovering the price formation mechanism of the stock index futures market and improving risk management capabilities.

Date: 2023
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DOI: 10.1080/1331677X.2022.2076144

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