Economic Policy Uncertainty and Stock Markets: A Multifractal Cross-Correlations Analysis

2021 ◽  
pp. 2150018
Author(s):  
Wei Jiang ◽  
Jianfeng Li ◽  
Guanglin Sun
Keyword(s):  
Economic Policy ◽  
Stock Markets ◽  
Composite Index ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Cross Correlation Analysis ◽  
The Us ◽  
Cross Correlations ◽  
The Cross ◽  
Underlying Mechanisms

We utilize the multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the cross-correlations between the US economic policy uncertainty (EPU) and US stock markets in the framework of Fractal Market Hypothesis (FMH). The data contain daily closing values of EPU, and the returns of Dow Jones Industrial Average Index (DJI), S&P 500 index (GSPC) and NASDAQ Composite Index (IXIC). Our empirical results show that changes in EPU and fluctuations in the US stock markets interact in a nonlinear way. Furthermore, there exists significant multifractality in the cross-correlations between EPU and stock markets. The cross-correlations exhibit dynamics and are affected by major international events. We capture the underlying mechanisms such as multifractality and nonlinear relation that dominate EPU-US stock markets nexus by means of FMH. The findings add a new dimension to the existing literature, and are important for market participants to adjust investment decisions.

A Multifractal Cross-Correlation Analysis of Economic Policy Uncertainty: Evidence from China and US

2021 ◽  
pp. 2150041
Author(s):  
Ruwei Zhao ◽  
Peng-Fei Dai
Keyword(s):  
Economic Policy ◽  
Correlation Analysis ◽  
Cross Correlation ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Economic Fluctuation ◽  
Cross Correlation Analysis ◽  
Uncertainty Index ◽  
Cross Correlations ◽  
Renyi Exponent

In this study, we utilized the prevailing economic policy uncertainty index (EPU) as the proxy of state economic fluctuation and investigated Sino–US economic fluctuation long horizon cross-correlation with a multifractal detrended cross-correlation analysis (MF-DCCA). With the MF-DCCA approach, we found a reliable long-range cross-correlation between China and US EPU changes. In addition, we discovered that a power law cross-correlation existed for the variation of most scaling orders. However, no persistence of cross-correlations was detected within the Sino–US EPU change series. Additionally, we implemented Rényi exponent and spectrum singularity checks. Both the examination results proved series multifractality with the presented arch-shaped curves. We further calculated the Hölder exponent bounds within each series and found that the China EPU changes had maximal multifractality with the largest exponent difference.

Economic policy uncertainty and stock markets: Long-run evidence from the US

2016 ◽  
Vol 18 ◽  
pp. 136-141 ◽  
Author(s):  
Mohamed Arouri ◽  
Christophe Estay ◽  
Christophe Rault ◽  
David Roubaud
Keyword(s):  
Economic Policy ◽  
Stock Markets ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Long Run ◽  
The Us

scholarly journals Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter?

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Manel Youssef ◽  
Khaled Mokni ◽  
Ahdi Noomen Ajmi
Keyword(s):  
Economic Policy ◽  
Stock Markets ◽  
Investment Banks ◽  
Individual Investors ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Daily Data ◽  
The Us ◽  
Portfolio Managers ◽  
The Uk

AbstractThis study investigates the dynamic connectedness between stock indices and the effect of economic policy uncertainty (EPU) in eight countries where COVID-19 was most widespread (China, Italy, France, Germany, Spain, Russia, the US, and the UK) by implementing the time-varying VAR (TVP-VAR) model for daily data over the period spanning from 01/01/2015 to 05/18/2020. Results showed that stock markets were highly connected during the entire period, but the dynamic spillovers reached unprecedented heights during the COVID-19 pandemic in the first quarter of 2020. Moreover, we found that the European stock markets (except Italy) transmitted more spillovers to all other stock markets than they received, primarily during the COVID-19 outbreak. Further analysis using a nonlinear framework showed that the dynamic connectedness was more pronounced for negative than for positive returns. Also, findings showed that the direction of the EPU effect on net connectedness changed during the pandemic onset, indicating that information spillovers from a given market may signal either good or bad news for other markets, depending on the prevailing economic situation. These results have important implications for individual investors, portfolio managers, policymakers, investment banks, and central banks.

US economic policy uncertainty spillover on the stock markets of the GCC countries

2020 ◽  
Vol 47 (1) ◽  
pp. 36-50 ◽  
Author(s):  
Khandokar Istiak ◽  
Md Rafayet Alam
Keyword(s):  
Economic Policy ◽  
Stock Market ◽  
Stock Markets ◽  
Risk Sharing ◽  
Financial System ◽  
Policy Uncertainty ◽  
Content Type ◽  
Economic Policy Uncertainty ◽  
Gcc Countries ◽  
The Us

PurposeThis study aims to investigate the nature and degree of US economic policy uncertainty spillover on the stock markets of a group of non-conventional economies like the Gulf Cooperation Council (GCC) countries, where a risk-sharing-based financial system is prominent and foreign investment, risk-free interest, derivatives, etc. are not as widespread as in the western economies.Design/methodology/approachthe monthly data of 1992–2018, linear and nonlinear structural vector autoregression (VAR) model, and an impulse response-based test to explore the nature and degree of US economic policy uncertainty spillover on the stock markets of the GCC countries.FindingsThis study finds that an unexpected increase in the US economic policy uncertainty significantly decreases the stock market index of all the GCC countries. This study also gets this relationship symmetric, meaning that the GCC stock market indices decrease and increase by the same amount when the US economic policy uncertainty increases and decreases, respectively.Originality/valueThis study investigates the characteristics of economic policy uncertainty spillover from the biggest economy of the world to the stock markets of the GCC region, which is new to the literature. The study results provide the first evidence that a risk-sharing based financial system does not necessarily protect the stock market from US uncertainty shock. However, the abundance of local investors, risk-sharing investment activities, the absence of derivatives, etc. may be responsible for the symmetric behavior of a stock market.

Multifractal Fluctuation Analysis of Correlations Between the Sector Stock Markets in China and the US

2020 ◽  
pp. 2150031
Author(s):  
You-Shuai Feng ◽  
Hong-Yong Wang
Keyword(s):  
Correlation Analysis ◽  
Stock Markets ◽  
Cross Correlation ◽  
Rapid Development ◽  
Fluctuation Analysis ◽  
Cross Correlation Analysis ◽  
The Us ◽  
Cross Correlations ◽  
The Cross ◽  
Stock Indexes

With the rapid development of economic globalization, the stock markets in China and the US are increasingly linked. The fluctuation features and cross-correlations of the two countries’ markets have attracted extensive attention from market investors and researchers. In this paper, the fractal analysis methods including multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) and coupled detrended cross-correlation analysis (CDCCA) are applied to explore the volatilities of CSI300 and SP500 sector stock indexes as well as the cross-correlations and coupling cross-correlations between the two corresponding sector stock indexes. The results show that the auto-correlations, cross-correlations and coupling cross-correlations have multifractal fluctuation characteristics, and that the cross-correlations are asymmetric. Additionally, the coupling cross-correlation strengths are distinct due to the different influence of long-range correlations and fat-tailed distribution. Further, the co-movement between China and the US sector stock markets is susceptible to external market factors such as major economic events and national policies.

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