What does the China's economic recovery after COVID-19 pandemic mean for the economic growth and energy consumption of other countries?

Following the financial crisis of 2007–2008, a deep analogy between the origins of instability in financial systems and complex ecosystems has been pointed out: in both cases, topological features of network structures influence how easily distress can spread within the system. However, in financial network models, the details of how financial institutions interact typically play a decisive role, and a general understanding of precisely how network topology creates instability remains lacking. Here we show how processes that are widely believed to stabilize the financial system, that is, market integration and diversification, can actually drive it towards instability, as they contribute to create cyclical structures which tend to amplify financial distress, thereby undermining systemic stability and making large crises more likely. This result holds irrespective of the details of how institutions interact, showing that policy-relevant analysis of the factors affecting financial stability can be carried out while abstracting away from such details.

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Pathways towards instability in financial networks

Time-varying spillover effects and investment strategies between WTI crude oil, natural gas and Chinese stock markets related to belt and road initiative

Effect of COVID-19 on the Relationship Between Euro/USD Exchange Rate and Oil Price

Using an event study methodology and a sample of 478 firms listed on the Australian Securities Exchange, we find the following results. First, coronavirus fear significantly and adversely affected the returns of many sectors, small-, medium- and large-sized stocks. Second, coronavirus fear was a source of return drift in the Australian stock market. Our results suggest that investors underreacted to coronavirus fear, and this underreaction was prevalent across a range of sectors and firm size categories. We also find that had investors adopted a short selling strategy for stocks that suffered significant negative effects from the coronavirus fear and post-event return drift, they would have gained profits ranging from 2.14% to 13.81%. Robustness tests based on longer event windows confirm the main results. Additionally, we find evidence of reversals in stock returns mostly following the first stimulus payment in Australia. However, large firms and the information technology sector were the first to experience a reversal in returns a few days following the announcement of the second stimulus package and the commencement of lockdown but before the first stimulus payment was made.

Effect of coronavirus fear on the performance of Australian stock returns: Evidence from an event study

Spillover Effects of RMB Exchange Rate among B&R Countries: before and during COVID-19 Event

The stock market is a complex system with unpredictable stock price fluctuations. When the positive feedback in the market amplifies, the systemic risk will increase rapidly. During the last 30 years of development, the mechanism and governance system of China’s stock market have been constantly improving, but irrational shocks have still appeared suddenly in the last decade, making investment decisions risky. Therefore, based on the daily return of all a-shares in China, this paper constructs a dynamic complex network of individual stocks, and represents the systemic risk of the market using the average weighting degree, as well as the adjusted structural entropy, of the network. In order to eliminate the influence of disturbance factors, empirical mode decomposition (EMD) and grey relational analysis (GRA) are used to decompose and reconstruct the sequences to obtain the evolution trend and periodic fluctuation of systemic risk. The results show that the systemic risk of China’s stock market as a whole shows a downward trend, and the periodic fluctuation of systemic risk has a long-term equilibrium relationship with the abnormal fluctuation of the stock market. Further, each rise of systemic risk corresponds to external factor shocks and internal structural problems.

https://www.mdpi.com/1099-4300/22/6/614/pdf

The Evolution Characteristics of Systemic Risk in China's Stock Market Based on a Dynamic Complex Network.

In the context of vigorously developing a low-carbon economy and facing the realistic situation of "double carbon goals", the government, as the leader of a country's economic development, should play a leading role in policy. However, at present, the relevant policy tools of our government still have many deficiencies. By studying the analysis of Chinese and foreign scholars on the current low-carbon economic measures of various countries in the world, this paper puts forward constructive suggestions on three aspects: property right policy tools, tax policy tools and legal policy tools. First, the government should promote the further improvement of the carbon emissions trading market, so as to improve China's carbon tax system. At the same time, with tax incentives as the main means, it is hoped that the government will implement legislation on carbon emissions trading through legislation. It is hoped that the government can follow the basic laws of the low-carbon economy, so that the above policy recommendations can be adopted and applied to the future development of the low-carbon economy, so as to achieve the goal of the low-carbon economy.

https://www.atlantis-press.com/article/125974452.pdf

Suggestions on the Way Government Policy Tools Play a Role in China’s Low-Carbon Economy

The ongoing COVID-19 pandemic has evolved beyond being a public health crisis as it has exerted worldwide severe economic impacts, triggering cascading failures in the global industrial network. Although certain powerful enterprises can remain its normal operation during this global shock, what's more likely to happen for the majority, especially those small- and medium-sized firms, is that they are experiencing temporary suspension out of epidemic control requirement, or even permanent closure due to chronic business losses. For those enterprises that sustain the pandemic and only suspend for a relatively short period, they could resume work and production when epidemic control and prevention conditions are satisfied and production and operation are adjusted correspondingly. In this paper, we develop a novel quantitative framework which is based on the classic susceptible-infectious-recovered (SIR) epidemiological model (i.e., the SIR model), containing a set of differential equations to capture such enterprises' reactions in response to COVID-19 over time. We fit our model from the resumption of work and production (RWP) data on industrial enterprises above the designated size (IEDS). By modeling the dynamics of enterprises' reactions, it is feasible to investigate the ratio of enterprises' state of operation at given time. Since enterprises are major economic entities and take responsibility for most output, this study could potentially help policy makers better understand the economic impact caused by the pandemic and could be heuristic for future prevention and resilience-building strategies against suchlike outbreaks of public health crises.

Zili Huang

Papers

Spillover Effects of RMB Exchange Rate among B&R Countries: before and during COVID-19 Event

The Evolution Characteristics of Systemic Risk in China's Stock Market Based on a Dynamic Complex Network.

Suggestions on the Way Government Policy Tools Play a Role in China’s Low-Carbon Economy

Modeling the resumption of work and production of enterprises during COVID-19: An SIR-based quantitative framework