Forecasting Chinese Stock Market Volatility With Intraday and Overnight Volatility Components of INE Oil Futures

ABSTRACT This paper investigates the role of different volatility components of the Shanghai International Energy Exchange (INE) oil futures, including intraday, overnight, and the first half‐hour components, in forecasting Chinese stock market volatility. Using 5‐min realized volatility (RV) as realized volatility measure (RM), the log‐HAR models are applied to generate one‐step‐ahead forecasts for three Chinese stock indices (CSI 300, SHSE and SZSE). Our out‐of‐sample results show that the model extended with 5‐min RV of INE oil futures does not generate more accurate volatility forecasts than the baseline log‐HAR model. However, the overnight volatility of INE oil futures significantly improves forecasting accuracy. Our results are robust across different estimation schemes, estimation windows, out‐of‐sample periods, and evaluation methods. Additionally, using Bi‐Power Variation (BPV) as an alternative RM yields consistent results. Overall, the results highlight the importance of incorporating the overnight volatility component of INE oil futures in forecasting Chinese stock market volatility.

Authors

Institutions

Publication Details

Journal
Journal of Futures Markets
Published
2025-07-20
DOI
https://doi.org/10.1002/fut.70008
Citations
2
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
6.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Forecasting Chinese Stock Market Volatility With Intraday and Overnight Volatility Components of INE Oil Futures

Zhuo Huang, Qihao Chen
2 citations
Journal of Futures Markets
Market Dynamics and Volatility
6.26
article

Forecasting Chinese Stock Market Volatility With Intraday and Overnight Volatility Components of INE Oil Futures

Zhuo Huang, Qihao Chen
article en
2 citations

Abstract

ABSTRACT This paper investigates the role of different volatility components of the Shanghai International Energy Exchange (INE) oil futures, including intraday, overnight, and the first half‐hour components, in forecasting Chinese stock market volatility. Using 5‐min realized volatility (RV) as realized volatility measure (RM), the log‐HAR models are applied to generate one‐step‐ahead forecasts for three Chinese stock indices (CSI 300, SHSE and SZSE). Our out‐of‐sample results show that the model extended with 5‐min RV of INE oil futures does not generate more accurate volatility forecasts than the baseline log‐HAR model. However, the overnight volatility of INE oil futures significantly improves forecasting accuracy. Our results are robust across different estimation schemes, estimation windows, out‐of‐sample periods, and evaluation methods. Additionally, using Bi‐Power Variation (BPV) as an alternative RM yields consistent results. Overall, the results highlight the importance of incorporating the overnight volatility component of INE oil futures in forecasting Chinese stock market volatility.

Journal of Futures MarketsVol. 45(10)
Peking University (CN), Beijing Institute of Big Data Research (CN)
Openalex Percentile: Top 4%
Market Dynamics and Volatility
6.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.