2020 ◽  
pp. 1-30
Author(s):  
LINGLING QIAN ◽  
YUEXIANG JIANG ◽  
HUAIGANG LONG ◽  
RUOYI SONG

We are the first to explore the effect of economic policy uncertainty (EPU) and the COVID-19 pandemic on the correlation between the cryptocurrency index CRIX and the world stock market portfolio, as well as the hedging properties of CRIX. To this end, we mainly apply the dynamic conditional correlation model with mixed data sampling regressions, a threshold vector autoregressive model and the generalized impulse response function. We demonstrate that the correlation is influenced by the uncertainty stance of the economy and behaves differently in low-, medium- and high-uncertainty periods. Most of the abnormal market relations exist in high levels of EPU or during the COVID-19 period, and the impact of global EPU is greater than that of EPU originating in the United States, Europe, Russia and China. Moreover, the CRIX can serve as a hedge asset against the world stock market. The high (low) level of EPU has a significantly positive (negative) effect on the optimal hedge ratio of CRIX, which increases significantly during the COVID-19 period. Our findings have implications for risk management, portfolio allocations and hedging strategies.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xinyu Wu ◽  
Tianyu Liu ◽  
Haibin Xie

Intraday range (the difference between intraday high and low prices) is often used to measure volatility, which has proven to be a more efficient volatility estimator than the return-based one. Meanwhile, a growing body of studies has found that economic policy uncertainty (EPU) has important impact on stock market volatility. In this paper, building on the range-based volatility model, namely, the conditional autoregressive range (CARR) model, we introduce the CARR-mixed-data sampling (CARR-MIDAS) model framework by considering intraday information to investigate the impact of EPU on the volatility of Chinese stock market and to explore the predictive ability of EPU for Chinese stock market. The empirical results show that both the China EPU (CEPU) and global EPU (GEPU) have a significantly negative effect on the long-run volatility of Chinese stock market. Furthermore, we find that taking into account the CEPU and GEPU leads to substantial improvement in the ability to forecast the volatility of Chinese stock market. We also find that the CEPU provides superior volatility forecasts compared to the GEPU. Our findings are robust to different forecasting windows.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Peng-Fei Dai ◽  
Xiong Xiong ◽  
Zhifeng Liu ◽  
Toan Luu Duc Huynh ◽  
Jianjun Sun

AbstractThis paper investigates the impact of economic policy uncertainty (EPU) on the crash risk of US stock market during the COVID-19 pandemic. To this end, we use the GARCH-S (GARCH with skewness) model to estimate daily skewness as a proxy for the stock market crash risk. The empirical results show the significantly negative correlation between EPU and stock market crash risk, indicating the aggravation of EPU increase the crash risk. Moreover, the negative correlation gets stronger after the global COVID-19 outbreak, which shows the crash risk of the US stock market will be more affected by EPU during the epidemic.


Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1411
Author(s):  
Xiaqing Su ◽  
Zhe Liu

Following generalized variance decomposition, we identify the transmission structure of financial shock among ten sectors in China. Then, we examine whether economic policy uncertainty (EPU) affects it through GARCH-MIDAS regression. We find that consumer discretionary, industrials, and materials sectors are systemically important industries during the sample period. Further research of dynamic analysis shows that each sector acts in a time-varying role in this structure. The results of the GARCH-MIDAS regression indicate that none of the selected EPU indexes has a significant long-term impact on the total volatility spillover of the inter-sector stock market in China. However, the EPUs do affect some sectors’ spillover indexes in the long run, and they are significantly heterogeneous. This paper can provide regulatory suggestions for policymakers and reasonable asset allocation and risk avoidance methods for investors.


2021 ◽  
Vol 13 (11) ◽  
pp. 5866
Author(s):  
Muhammad Khalid Anser ◽  
Qasim Raza Syed ◽  
Hooi Hooi Lean ◽  
Andrew Adewale Alola ◽  
Munir Ahmad

Since the turn of twenty first century, economic policy uncertainty (EPU) and geopolitical risk (GPR) have escalated across the globe. These two factors have both economic and environmental impacts. However, there exists dearth of literature that expounds the impact of EPU and GPR on environmental degradation. This study, therefore, probes the impact of EPU and GPR on ecological footprint (proxy for environmental degradation) in selected emerging economies. Cross-sectional dependence test, slope heterogeneity test, Westerlund co-integration test, fully modified least ordinary least square estimator, dynamic OLS estimator, and augmented mean group estimator are employed to conduct the robust analyses. The findings reveal that EPU and non-renewable energy consumption escalate ecological footprint, whereas GPR and renewable energy plunge ecological footprint. In addition, findings from the causality test reveal both uni-directional and bi-directional causality between a few variables. Based on the findings, we deduce several policy implications to accomplish the sustainable development goals in emerging economies.


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