There is an increasing influence of machine learning in business applications, with many solutions already implemented and many more being explored. Since the global financial crisis, risk management in banks has gained more prominence, and there has been a constant focus around how risks are...

Risk diversification is the basis of insurance and investment. It is thus crucial to study the effects that could limit it. One of them is the existence of systemic risk that affects all of the policies at the same time. We introduce here a probabilistic approach to examine the consequences of...

Over the last three decades, the world economy has been facing stock market crashes, currency crisis, the dot-com and real estate bubble burst, credit crunch and banking panics. As a response, extreme value theory (EVT) provides a set of ready-made approaches to risk management analysis....

The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is...

The question of whether environmental, social, and governance investments outperform or underperform other conventional financial investments has been debated in the literature. In this study, we compare the volatility of rates of return of selected ESG indices and conventional ones and...

Risk taking is an inherent element of the banking business. Banks make conscious decisions regarding risk taking as they expect to make more return if they take more risk. The primary objective of this study is to empirically investigate the efficiency of Indian banks in generating return...

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in Polish cooperative banks on the example of banks...

The relevance of the development is determined by the possibility of testing a complex analytical methodology for forecasting the daily volatility of Bulgarian investment funds, which will support the investment community in making adequate investment decisions. The used risk attribution...

This study aims at developing econometric models to manage the price risk of Dry and Wet Cocoa beans with the help of ARIMA (Autoregressive Integrated Moving Average) and VAR (Vector Auto Regressive). The monthly price of Cocoa beans is collected for the period starting from April 2009 to March...

In this paper, we employ 99% intraday value-at-risk (VaR) and intraday expected shortfall (ES) as risk metrics to assess the competency of the Multiplicative Component Generalised Autoregressive Heteroskedasticity (MC-GARCH) models based on the 1-min EUR/USD exchange rate returns. Five...