Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators

被引：6

作者：

Zhang, Lixia ^{[1
,5
]}

Bai, Jiancheng ^{[1
,2
,5
]}

Zhang, Yueyan ^{[3
,6
]}

Cui, Can ^{[4
,7
]}

机构：

[1] Yancheng Teachers Univ, Sch Business, Yancheng 224007, Peoples R China

[2] Nantong Univ, Jiangsu Yangtze River Econ Belt Res Inst, Nantong 226019, Peoples R China

[3] Gingko Coll Hospitality Management, Dept Business Adm, Chengdu 611730, Peoples R China

[4] China Minsheng Banking Corp, Nanjing 211100, Peoples R China

[5] 2 South Hope Dadao Rd, Yancheng, Jiangsu, Peoples R China

[6] 111,North 1st Sect,Second Ring Rd, Chengdu, Sichuan, Peoples R China

[7] 20 Hongwu North Rd, Nanjing, Jiangsu, Peoples R China

来源：

RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE | 2023年 / 65卷

关键词：

World economic situation; Global economic condition (GECON) index; Stock market volatility; Generalized autoregressive conditional; heteroskedasticity (GARCH) -mixed-data; sampling (MIDAS) modeling; PRICE VOLATILITY;

D O I：

10.1016/j.ribaf.2023.101949

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

We comparatively assess the influence of global economic uncertainty measures on Chinese stock market volatility. Using a model based on generalized autoregressive conditional hetero-skedasticity and mixed-data sampling, the results show that the global economic policy uncer-tainty index, the geopolitical risk index, and the global economic condition index all significantly influence the long-term volatility of China's equity market. We highlight which of these measures has the most explanatory power under differing contexts. As uncertainty measures have wide applicability, investors, policymakers, and academicians will be quite interested in our results.

引用

页数：11

共 52 条

[1] Identifying diversifiers, hedges, and safe havens among Asia Pacific equity markets during COVID-19: New results for ongoing portfolio allocation [J].

Ali, Fahad ;

Sensoy, Ahmet ;

Goodell, John W. .

INTERNATIONAL REVIEW OF ECONOMICS & FINANCE, 2023, 85 :744-792

[2] The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH-MIDAS Approach [J].

Asgharian, Hossein ;

Hou, Ai Jun ;

Javed, Farrukh .

JOURNAL OF FORECASTING, 2013, 32 (07) :600-612

[3] Are energy markets informationally smarter than equity markets? Evidence from the COVID-19 experience [J].

Ashok, Shruti ;

Corbet, Shaen ;

Dhingra, Deepika ;

Goodell, John W. ;

Kumar, Satish ;

Yadav, Miklesh Prasad .

FINANCE RESEARCH LETTERS, 2022, 47

[4] Measuring Economic Policy Uncertainty [J].

Baker, Scott R. ;

Bloom, Nicholas ;

Davis, Steven J. .

QUARTERLY JOURNAL OF ECONOMICS, 2016, 131 (04) :1593-1636

[5]

Balcilar Mehmet., 2016, ECONOMICS-KIEL, V10, P1, DOI DOI 10.5018/ECONOMICS-EJOURNAL.JA.2016-27

[6] Energy Markets and Global Economic Conditions [J].

Baumeister, Christiane ;

Korobilis, Dimitris ;

Lee, Thomas K. .

REVIEW OF ECONOMICS AND STATISTICS, 2022, 104 (04) :828-844

[7] A comparison of monthly global indicators for forecasting growth [J].

Baumeister, Christiane ;

Guerin, Pierre .

INTERNATIONAL JOURNAL OF FORECASTING, 2021, 37 (03) :1276-1295

[8] Host country institutions and firm-level R&D influences: An analysis of European Union FDI in China [J].

Cai, Huifen ;

Boateng, Agyenim ;

Guney, Yilmaz .

RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2019, 47 :311-326

[9] Measuring Geopolitical Risk [J].

Caldara, Dario ;

Iacoviello, Matteo .

AMERICAN ECONOMIC REVIEW, 2022, 112 (04) :1194-1225

[10] Chinese stock market volatility and the role of US economic variables [J].

Chen, Jian ;

Jiang, Fuwei ;

Li, Hongyi ;

Xu, Weidong .

PACIFIC-BASIN FINANCE JOURNAL, 2016, 39 :70-83

← 1 2 3 4 5 6 →