scholarly journals Comparison of Complex Networks of Stock Markets and Economic Variables in the Period Before and After the Outbreak of Coronavirus (Covid-19)

2020 ◽  
Vol 10 (40) ◽  
pp. 123-158
Author(s):  
Matin Saneifar ◽  
Parviz Saeedi ◽  
◽  
Keyword(s):  
Complex Networks ◽  
Stock Markets ◽  
Economic Variables ◽  
Before And After

scholarly journals Network robustness improvement via long-range links

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Vincenza Carchiolo ◽  
Marco Grassia ◽  
Alessandro Longheu ◽  
Michele Malgeri ◽  
Giuseppe Mangioni
Keyword(s):  
Complex Networks ◽  
Long Range ◽  
Real World ◽  
Network Robustness ◽  
Scale Free ◽  
Area Of Interest ◽  
Before And After ◽  
Significant Area ◽  
Better Than

AbstractMany systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies.

Are Shocks Asymmetric to Volatility of Chinese Stock Markets?

2004 ◽  
Vol 07 (03) ◽  
pp. 379-395 ◽  
Author(s):  
Wei-Chiao Huang ◽  
Yuanlei Zhu
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Garch Model ◽  
Leverage Effect ◽  
Arch Models ◽  
Before And After ◽  
Chinese Markets ◽  
Chinese Stock Markets ◽  
Better Than ◽  
A Share

This paper uses ARCH models to examine if there is a leverage effect and also to test if A- and B-share holdings have different risks in Chinese stock markets before and after B-share markets open to domestic investors in February 2001. The empirical results suggest that leverage effect was not present and shocks have symmetric impact on the volatility of Chinese B-share stock returns in both periods and A-share returns in Period I. Thus GARCH model would be a better model to fit the Chinese B-share stock returns than EGARCH or GJR-GARCH model. But EGARCH or GJR-GARCH model fits recent (Period II) A-share markets data better than GARCH model. Another finding of this paper is that holding A- or B-share bears different risk in returns in the two Chinese markets. Furthermore, news or shocks have a larger impact on volatility of B-share returns in Period I than in Period II.

scholarly journals Contagion of the Subprime Financial Crisis on Frontier Stock Markets: A Copula Analysis

Economies ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 15 ◽  
Author(s):  
Wahbeeah Mohti ◽  
Andreia Dionísio ◽  
Paulo Ferreira ◽  
Isabel Vieira
Keyword(s):  
Financial Crisis ◽  
Stock Markets ◽  
Large Set ◽  
Subprime Crisis ◽  
Relative Level ◽  
Copula Models ◽  
Before And After ◽  
The Usa ◽  
International Investors ◽  
Geographical Diversification

This study assesses contagion from the USA subprime financial crisis on a large set of frontier stock markets. Copula models were used to investigate the structure of dependence between frontier markets and the USA, before and after the occurrence of the crisis. Statistically significant evidence of contagion could only be found in the European region, with the markets of Croatia and Romania being affected. The remaining European markets in our sample and the others, located in America, Middle East, Africa, and Asia, appear to have been isolated from the subprime crisis impact. These results are useful for international investors interested in enlarging the geographical diversification of their portfolios, but also for the considered countries’ policymakers who should attempt to improve the attractiveness of stock markets for domestic and foreign investors while simultaneously attempting to maintain their relative level of insulation against future foreign crises.

scholarly journals Oil and stock markets before and after financial crises: A local Gaussian correlation approach

2017 ◽  
Vol 37 (12) ◽  
pp. 1179-1204 ◽  
Author(s):  
Georgios Bampinas ◽  
Theodore Panagiotidis
Keyword(s):  
Stock Markets ◽  
Financial Crises ◽  
Before And After

Stock Market Linkages Before and After the Asian Financial Crisis: Evidence from Three Greater China Economic Area Stock Markets and the US

2006 ◽  
Vol 09 (02) ◽  
pp. 297-315 ◽  
Author(s):  
Hwahsin Cheng ◽  
John L. Glascock
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
The United States ◽  
Asian Financial Crisis ◽  
Greater China ◽  
Market Linkages ◽  
Economic Area ◽  
Before And After

We investigate the stock market linkages between the United States and three Greater China Economic Area stock markets — China, Hong Kong, and Taiwan, before and after the 1997 Asian financial crisis. Daily stock market indices from January 1995 to December 2000 are used for the analysis. Results from Granger causality test indicate increased feedback relationships between the markets in the post-crisis period. We also find, from the principal component analysis, fewer common factors affecting stock returns after the crisis, suggesting more harmonious market co-movements after the financial crisis. Additionally, results from a variance decomposition analysis suggest that stock markets are more responsive to foreign shocks after the crisis. This further strengthens the evidence that stock markets become more interrelated after the 1997 Asian financial crisis.

Effect of landslides on the structural characteristics of land-cover based on complex networks

2017 ◽  
Vol 31 (22) ◽  
pp. 1750156 ◽  
Author(s):  
Jing He ◽  
Chuan Tang ◽  
Gang Liu ◽  
Weile Li
Keyword(s):  
Land Cover ◽  
Complex Networks ◽  
Power Law ◽  
Satellite Images ◽  
Structural Characteristics ◽  
Power Law Distribution ◽  
Graph Topology ◽  
Linear Coefficient ◽  
Area Distribution ◽  
Before And After

Landslides have been widely studied by geologists. However, previous studies mainly focused on the formation of landslides and never considered the effect of landslides on the structural characteristics of land-cover. Here we define the modeling of the graph topology for the land-cover, using the satellite images of the earth’s surface before and after the earthquake. We find that the land-cover network satisfies the power-law distribution, whether the land-cover contains landslides or not. However, landslides may change some parameters or measures of the structural characteristics of land-cover. The results show that the linear coefficient, modularity and area distribution are all changed after the occurence of landslides, which means the structural characteristics of the land-cover are changed.

scholarly journals Impact of Covid-19 in Bangladesh Stock Market

2020 ◽  
Vol 4 (2) ◽  
pp. 22-23
Author(s):  
Sunjida Haque ◽  
Tanbir Ahmed Chowdhury
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Stock Exchange ◽  
Potential Consequence ◽  
Economic Activities ◽  
Market Data ◽  
Policy Interventions ◽  
The World ◽  
Before And After ◽  
The Impact

The world's big economies are roiled and going under a devastating threat amid the impact of the COVID-19 pandemic. No country will be safe as this virus will eventually outbreak everywhere, regardless of how countries prepare to avoid it. The economic ramification as well as the stock market crisis will be uncertain due to the extended suspension of economic activities in almost every country. No wonder, the clattered stock markets of Bangladesh which have already got the adjective of “the worst stock market in the world” because of inefficient and irrational fluctuations in previous years will experience a colossal crisis due to the pandemic. The article provides an investigation on comparable analysis of the impact on stock markets of Bangladesh, Dhaka stock exchange, and Chittagong stock exchange, before and after the pandemic situation with current market data. We also examine the potential consequence of policy interventions to the market and the investors during a pandemic.

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