Indices de stabilité financière et dynamique des réseaux financiers en Europe

Chabot, Miia

doi:10.3917/reco.724.0591

Cited by 4 publications

(1 citation statement)

References 78 publications

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“…Network analysis of correlations is a well-established methodology, which has been applied widely to several topics. For example, in financial networks, the analysis of the relevant networks is useful for the study of risk contagion in financial markets [23][24][25][26][27][28], while in brain networks, the relevant correlation networks have been analyzed as signed graphs [29]. Recently, network analysis has been applied to the relationships between the Sustainable Development Indicators.…”

Section: Introductionmentioning

confidence: 99%

Correlations of ESG Ratings: A Signed Weighted Network Analysis

et al. 2022

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ESG ratings are data-driven indices, focused on three key pillars (Environmental, Social, and Governance), which are used by investors in order to evaluate companies and countries, in terms of Sustainability. A reasonable question which arises is how these ratings are associated to each other. The research purpose of this work is to provide the first analysis of correlation networks, constructed from ESG ratings of selected economies. The networks are constructed based on Pearson correlation and analyzed in terms of some well-known tools from Network Science, namely: degree centrality of the nodes, degree centralization of the network, network density and network balance. We found that the Prevalence of Overweight and Life Expectancy are the most central ESG ratings, while unexpectedly, two of the most commonly used economic indicators, namely the GDP growth and Unemployment, are at the bottom of the list. China’s ESG network has remarkably high positive and high negative centralization, which has strong implications on network’s vulnerability and targeted controllability. Interestingly, if the sign of correlations is omitted, the above result cannot be captured. This is a clear example of why signed network analysis is needed. The most striking result of our analysis is that the ESG networks are extremely balanced, i.e. they are split into two anti-correlated groups of ESG ratings (nodes). It is impressive that USA’s network achieves 97.9% balance, i.e. almost perfect structural split into two anti-correlated groups of nodes. This split of network structure may have strong implications on hedging risk, if we see ESG ratings as underlying assets for portfolio selection. Investing into anti-correlated assets, called as "hedge assets", can be useful to offset potential losses. Our future direction is to apply and extend the proposed signed network analysis to ESG ratings of corporate organizations, aiming to design optimal portfolios with desired balance between risk and return.

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Section: Introductionmentioning

confidence: 99%

Correlations of ESG Ratings: A Signed Weighted Network Analysis

et al. 2022

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Climate risks and financial stability: Evidence from the European financial system

Chabot,

Bertrand

2023

Journal of Financial Stability

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Impact of interest rate, exchange rate, and inflation on commercial banks’ performance

Merko

Habili²

2023

CBSR

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This study aims to measure the impact of interest rates, exchange rates, and inflation on the performance of commercial banks in Albania, using monthly data from December 2015 to May 2022 obtained from the Bank of Albania and the Institute of Statistics of Albania (INSTAT). The multiple regression model measures the relationship between the dependent variable (ROA) and independent variables (inflation, interest rate, and exchange rate). The estimation results reveal that the interest rate variability has a high impact on the financial factor ROA. In contrast, the variability of the exchange rate harms it. The effect of variable nominal effective exchange rate (NEER) on ROA is low, and inflation negatively influences it. The model has resulted within all the criteria related to the regression analysis but with a low importance level. The important conclusion of this study is that the combination of variables, inflation, exchange rate, and interest rate, does not measure the impact of inflation on the performance of commercial banks. Other micro and macroeconomic factors can measure this impact.

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Indices de stabilité financière et dynamique des réseaux financiers en Europe

Cited by 4 publications

References 78 publications

Correlations of ESG Ratings: A Signed Weighted Network Analysis

Correlations of ESG Ratings: A Signed Weighted Network Analysis

Climate risks and financial stability: Evidence from the European financial system

Impact of interest rate, exchange rate, and inflation on commercial banks’ performance

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