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Applied Economics Volume 53, 2021 - Issue 22
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Research Article

The role of high-frequency data in volatility forecasting: evidence from the China stock market

Min Liua School of Economics and Management, Nanchang University, Nanchang, China;b School of Business and Economics, Universiti Putra Malaysia, MalaysiaView further author information
,
Chien-Chiang Leea School of Economics and Management, Nanchang University, Nanchang, China;c Research Center of the Central China for Economic and Social Development, Nanchang University, ChinaORCID Iconhttps://orcid.org/0000-0003-0037-4347View further author information
ORCID Icon &
Wei-Chong Choob School of Business and Economics, Universiti Putra Malaysia, MalaysiaCorrespondence[email protected]
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Pages 2500-2526 | Published online: 17 Jan 2021

Citations (15)

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Read on this site (3)

Tian Ma, Cunfei Liao & Fuwei Jiang. (2023) Global, Developed and Emerging Stock Market: Which Characteristic Matters?. Emerging Markets Finance and Trade 59:8, pages 2617-2636.
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Mengxi He, Yaojie Zhang, Danyan Wen & Yudong Wang. (2022) Forecasting the Chinese stock market volatility: A regression approach with a t-distributed error. Applied Economics 54:50, pages 5811-5826.
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Zhengxun Tan, Jihai Yang, Yihong Ma & Juan Liu. Detecting turning points of stock markets in China and the United States. Applied Economics 0:0, pages 1-20.
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Articles from other publishers (12)

Yirong Huang & Yi Luo. (2024) Forecasting conditional volatility based on hybrid GARCH-type models with long memory, regime switching, leverage effect and heavy-tail: Further evidence from equity market. The North American Journal of Economics and Finance 72, pages 102148.
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Min Liu, Tongji Guo, Weiying Ping & Liangqing Luo. (2023) Sustainability and stability: Will ESG investment reduce the return and volatility spillover effects across the Chinese financial market?. Energy Economics 121, pages 106674.
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Nor Azliana Aridi, Tan Siow Hooi & Chin Wen Cheong. A stylized facts comparison between low-frequency and high-frequency data of Brazil stock market index. A stylized facts comparison between low-frequency and high-frequency data of Brazil stock market index.
Chao Liang, Zhenglan Xia, Xiaodong Lai & Lu Wang. (2022) Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model. Energy Economics 116, pages 106437.
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Ying-Shu Hung, Chingnun Lee & Pei-Fen Chen. (2022) China’s monetary policy and global stock markets: A new cointegration approach with smoothing structural changes. Economic Analysis and Policy 76, pages 643-666.
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Bangzhu Zhu, Chunzhuo Wan & Ping Wang. (2022) Interval forecasting of carbon price: A novel multiscale ensemble forecasting approach. Energy Economics 115, pages 106361.
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Min Liu. (2022) The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic. Economic Analysis and Policy 75, pages 288-309.
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Min Liu & Chien-Chiang Lee. (2022) Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS. Resources Policy 76, pages 102703.
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Min Liu & Chien-Chiang Lee. (2021) Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting. Energy Economics 103, pages 105622.
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Tian Ma, Cunfei Liao & Fuwei Jiang. (2022) Dissecting Developed and Emerging Stock Market: Which Characteristic Matters?. SSRN Electronic Journal.
Crossref
Chien-Chiang Lee, Yanxin Fang & Min Liu. (2022) Analyzing the Nexus of Green Finance, Clean Energy, Green Technology and Environmental Responsibility: Evidence from the Dcc-Midas. SSRN Electronic Journal.
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Min Liu & Chien-Chiang Lee. (2022) Is Gold a Long-Run Hedge, Diversifier, or Safe Haven for Oil?  Empirical Evidence Based on Dcc-Midas. SSRN Electronic Journal.
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