Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

Predicting volatility is a must in the finance domain. Estimations of volatility, along with the central tendency, permit us to evaluate the chances of getting a particular result. Financial analysts are frequently challenged with the assignment of diversifying assets in order to form efficient...

For this paper, we dynamically analysed the comovements between three major stock markets-Germany, the UK, and the US-and the countries of the European Union, divided into two groups: Eurozone and non-Eurozone. Correlation coefficients based on a detrended cross-correlation analysis (DCCA) were...

We examined volatility spillover effects from five prominent global stock markets to India's stock market during the pre-and-post COVID-19 outbreak using daily adjusted closing prices between January 2019 and September 2021 from six capital markets. The structural breakpoint was identified as 23...

Background: Global environmental and social research strengthens the protection of people and the environment, develops national capacity for social and environmental management and enables significant progress in terms of transparency, accountability, nondiscrimination and public participation....

Immigration is a controversial topic that draws much debate. From a human sustainability perspective, immigration is disadvantageous for home countries causing brain drains. Ample evidence suggests the developed host countries benefit from immigration in terms of diversification, culture,...