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1 – 5 of 5Chao Ren, Xiaoxing Liu and Ziyan Zhu
The purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.
Abstract
Purpose
The purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.
Design/methodology/approach
This paper introduces a tractable guarantee network model that captures the invulnerability of the network in terms of cascade-based attack. Furthermore, the equilibrium points are introduced for banks to determine loan origination.
Findings
The proposed approach not only develops equilibrium analysis as an extended perspective in the guarantee network, but also applies cascading failure method to construct the guarantee network. The equilibrium points are examined by simulating experiment. The invulnerability of the guarantee network is quantified by the survival of firms in the simulating progress.
Research limitations/implications
There is less study in equilibrium analysis of the guarantee network. Additionally, cascading failure model is expressed in the presented approach. Moreover, agent-based model can be extended in generating the guarantee network in the future study.
Originality/value
The approach of this paper presents a framework to analyze the equilibrium of the guarantee network. For this, the systemic risk of the whole guarantee network and each node's contribution are measured to predict the probability of default on cascading failure. Focusing on cascade failure process based on equilibrium point, the invulnerability of the guarantee network can be quantified.
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Zeinab Rahimi Rise and Mohammad Mahdi Ershadi
This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts…
Abstract
Purpose
This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.
Design/methodology/approach
The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.
Findings
The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.
Practical implications
The proposed methods can be applied to conduct infectious diseases impacts analysis.
Originality/value
In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.
Highlights:
A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;
Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;
Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;
An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;
A real case study is considered to evaluate the performances of the proposed models.
A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;
Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;
Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;
An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;
A real case study is considered to evaluate the performances of the proposed models.
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Prince Kumar Maurya, Rohit Bansal and Anand Kumar Mishra
This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.
Abstract
Purpose
This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.
Design/methodology/approach
The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.
Findings
This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.
Originality/value
The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.
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Chiraz Ayadi and Houda Ben Said
This paper aims to explore the impact of the coronavirus on the volatility spillovers of 10 selected developed markets hit by this pandemic (e.g. the USA, Canada, Korea, Japan…
Abstract
Purpose
This paper aims to explore the impact of the coronavirus on the volatility spillovers of 10 selected developed markets hit by this pandemic (e.g. the USA, Canada, Korea, Japan, the UK, Germany, Italy, Spain, France and China).
Design/methodology/approach
The database consists of daily data from January 1, 2020, to December 31, 2022. The data used are the precise daily closing prices of various indices of selected markets gathered from the DataStream and Investing.com databases. The authors use the VAR model to study the transmission of volatility between stock markets and analyze the dynamic links between them. Then, the Granger causality test is used to study the volatility movements and determine which of these markets is likely to influence the others. Then, impulse response functions are used to understand the reactions of the studied markets following shocks in the two most important markets, namely, the American and Chinese markets. Finally, forecast errors variance decomposition is used to measure the dynamic interactions that characterize the relationships between the studied markets.
Findings
Empirical results reveal instability in the returns of various indexes and the existence of causal relationships between standardized volatility of markets. The reactions of some markets following a shock in American and Chinese markets differ among markets. The empirical results also show that forecast errors variance of some markets begin coming from their own innovations during first periods. These shares decrease then in favor of other markets interventions.
Practical implications
The findings have significant practical implications for governments around the world as well as for financial investors. The successful practice of China’s pandemic prevention and control efforts may inspire governments to determine how to overcome panic and strengthen confidence in victory. Policymakers can use the insights from our study to design more effective economic policies and regulations to mitigate the negative impact of future pandemics on the financial system. Regulators can use these results to identify areas of weakness in the financial system and take proactive measures to address them. Financial investors may use the outcomes of our result to better understand the impact of global pandemics on financial markets. They may know which markets are the most active, which ones are causing considerable effects on the others and which ones show resilience and an anti-risk capacity. This may help them to make appropriate decisions about their investments.
Originality/value
It has become imperative to estimate the impact of this pandemic on the behavior of financial markets to prevent the deterioration and dysfunction of the global financial system. The findings have important implications for financial investors and governments who should know which markets are the most shaken, which cause remarkable effects on others and which show resilience and anti-risk capacity. Countries could follow China in some measures taken to moderate the negative effects of this epidemic on national economies.
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Soumaya Ben Khelifa and Sonia Arsi
This paper aims to explore the impact of the COVID-19 pandemic on the market timing skills of Islamic equity funds in Asia, Europe and North America.
Abstract
Purpose
This paper aims to explore the impact of the COVID-19 pandemic on the market timing skills of Islamic equity funds in Asia, Europe and North America.
Design/methodology/approach
The authors employed a two-step process. First, a Granger causality test is applied to test the bivariate relationship between Islamic fund indices and stock market ones by highlighting the impact of the COVID-19 pandemic. Second, the methodology of Treynor and Mazuy (1966) is deployed to account for the market timing abilities skills of Islamic fund managers during the pandemic period.
Findings
The investigation revealed mixed results. The European Islamic funds were positively impacted by the stock market as well as by the COVID-19 pandemic context. Additionally, compared to their Asian and North American peers, only European Islamic fund managers have the ability to time the market during the health crisis period.
Research limitations/implications
Despite its contribution to the Islamic finance literature, this study has some flaws. Indeed, the selected sample of three regions, namely Asia, Europe and North America, precludes extrapolating these conclusions. Other regions should be investigated to further our understanding of Islamic equity funds. Furthermore, due to data availability and accessibility, the study period was limited to a specific time of the COVID-19 pandemic. This shortcoming can be addressed through a multiwave investigation, especially since each region was exposed differently to the pandemic.
Practical implications
The paper provides scholars, portfolio managers and investors with insights regarding the investment dilemma during the COVID-19 pandemic period, especially for those wishing to hedge their pandemic risk exposure and/or diversify their portfolios. Equally, the depiction of potential market timing abilities of Islamic fund managers across the three regions would serve as a guide to identifying the most suitable internationally focused investment strategy.
Social implications
The paper provides scholars, portfolio managers and investors with insights regarding the investment dilemma during the COVID-19 pandemic period, especially for those wishing to hedge their pandemic risk exposure and/or diversify their portfolios. Equally, the depiction of potential market timing abilities of Islamic funds managers across the three regions would serve as a guide to identify the most suitable internationally focused investment strategy.
Originality/value
The originality of this investigation is that it is the first to examine Islamic equity fund managers and their skills to time the stock markets during the COVID-19 pandemic period in Asia, Europe and North America. The current paper extends the Islamic finance literature.
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