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Economic uncertainty and stock market asymmetric volatility: analysis based on the asymmetric GARCH-MIDAS model

Zaifeng Wang (School of Finance, Dongbei University of Finance and Economics, Dalian, China)
Tiancai Xing (School of Finance, Monetary and Financial Research Institute, Dongbei University of Finance and Economics, Dalian, China)
Xiao Wang (School of Finance, Dongbei University of Finance and Economics, Dalian, China)

International Journal of Emerging Markets

ISSN: 1746-8809

Article publication date: 26 February 2024




We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.


We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.


Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Research limitations/implications

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Practical implications

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

Social implications

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.


This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.



Funding: This work was supported by the General Program of the National Natural Science Foundation of China [Grant Number: 71273042], Major Project of Humanities and Social Science Key Base of Ministry of Education [Grant Number: 13JJD790003] and the Major Commissioned Project of Liaoning Social Science Planning Fund [Grant Number: L21ZD024].


Wang, Z., Xing, T. and Wang, X. (2024), "Economic uncertainty and stock market asymmetric volatility: analysis based on the asymmetric GARCH-MIDAS model", International Journal of Emerging Markets, Vol. ahead-of-print No. ahead-of-print.



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