In recent years sustainable finance along with Environmental, Social and Governance (ESG) aspects and their implications for financial institutions have attracted the attention of academics and policy makers. The aim of the book is to bring together chapters that discuss the most recent empirical and theoretical evidence in the field, along with policy making and regulatory initiatives. The book covers topics such as the changing role of banks in the financial system, the differences between sustainable banks and traditional banks, ESG and financial performance, bank social responsibility and customer satisfaction, ESG risk management of financial institutions, the politics of climate finance and policy initiatives, and the role of bank regulators. It will be of interest to academics and policymakers working in banking, risk management, sustainable finance and related fields.

The vast volume of financial data that exists and the globalisation of financial markets create new challenges for researchers and practitioners in economics and finance. Computational data analysis techniques can contribute significantly within this context, by providing a rigorous analytic framework for decision-making and support, in areas such as financial times series analysis and forecasting, risk assessment, trading, asset management, and pricing. The aim of this edited volume is to present, in a unified context, some recent advances in the field, covering the theory, the methodologies, and the applications of computational data analysis methods in economics and finance. The volume consists of papers published in the fifth volume of the Journal of "Computational Optimization in Economics & Finance" (published by Nova Science Publishers). The contents of this volume cover a wide range of topics, including among others stock market applications, corporate finance, corporate performance, as well as macroeconomic issues.