Risk Assessment Methodology for Pit Lakes Instabilities

In this study we present a generic probabilistic risk assessment methodology to evaluate the risk associated with flooding process of a pit. We use the bow-tie analysis to analyze the critical events (we focus on slope failures) and the systemic risk assessment methodology to estimate the risk for the population, for the environment and for the infrastructure. Furthermore, we perform a spatial analysis of the risk by discretizing the affected area into squares, by estimating the risk in each one and finally by creating the risk map. The methodology is implemented by specialized software that has been created in a Matlab environment for the deduction of such risk assessments. The developed methodology was applied in the area of the pit lake Most in Czech Republic.

Systemic Risk-Driven Portfolio Selection

How can we construct portfolios that perform well in the face of systemic events? The global financial crisis of 2007–2008 and the coronavirus disease 2019 pandemic have highlighted the importance of accounting for extreme form of risks. In “Systemic Risk-Driven Portfolio Selection,” Capponi and Rubtsov investigate the design of portfolios that trade off tail risk and expected growth of the investment. The authors show how two well-known risk measures, the value-at-risk and the conditional value-at-risk, can be used to construct portfolios that perform well in the face of systemic events. The paper uses U.S. stock data from the S&P500 Financials Index and Canadian stock data from the S&P/TSX Capped Financial Index, and it demonstrates that portfolios accounting for systemic risk attain higher risk-adjusted expected returns, compared with well-known benchmark portfolio criteria, during times of market downturn.

What Factors Drive the Banks Systemic Risk among South Asian Countries

Purpose: This study designs to examine the determinants (size, liquidity ratio, leverage ratio, deposit ratio, asset growth, net interest income ratio and return on asset ratio) of bank’s systemic risk. We use the data of listed commercial banks of the South Asian countries (Pakistan, Bangladesh, and India). Design/Methodology/Approach: The sample consists 30 banks from Bangladesh, 87 banks from India and 22 banks from Pakistan. This study covers the period from 2006 to 2018. The data is collected from the published annual reports of banks and stock exchanges of respective country. The panel data analysis is performed for the estimation of research models. Findings: The findings demonstrate that larger banks contribute lower in the systemic risk of banks. Additionally, highly liquid banks enhance the systemic risk of the banking system. Moreover, the banks with greater reliance on the deposits, net interest income and with high return on asset reduce the systemic risk contribution of the banks. Implications/Originality/Value: This study provides the justification to devise the banking policies like enhance the proportion of liquidity among assets, reliance on net interest income and promote the financing needs through deposits to limit the systemic risk contribution of the banking system.