Reprint
Data Analysis for Risk Management – Economics, Finance and Business
Edited by
June 2024
264 pages
- ISBN978-3-7258-1416-9 (Hardback)
- ISBN978-3-7258-1415-2 (PDF)
This is a Reprint of the Special Issue Data Analysis for Risk Management – Economics, Finance and Business that was published in
Business & Economics
Computer Science & Mathematics
Summary
This reprint concerns methods of data analysis for risk management in economics, finance, and business. The presented papers contain research on data analysis methods, including classical statistical methods, and machine learning methods that have emerged from statistics and are being effectively applied using high-speed computers, considering the availability of big data.
Format
- Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
exchange rate volatility; currency misalignment; business cycle; central and eastern European countries; public management; risk management; public hospitals; financial stability; stakeholders’ engagement; survey research; Poland; systemic risk; systemic illiquidity; liquidity crisis; parametric models; quantitative methods; emerging markets; frontier markets; CEE; bancassurance; insurance; risk factors; default; bankruptcy risk; Poisson process; doubly stochastic assumption; ROC curve; accuracy ratio; leverage; new definition of default; credit risk models; Bayesian approach; ESG; risk management; volatility; GARCH; copula; tail dependence; systemic risk; banking sector; DCoVaR; MES; SRISK; quantile regression; EGARCH; DCC; value at risk; credit scorecard development; open source; R; neural network; stock exchange; accounting systems; finance; credit scoring; ROC curve; Gini coefficient; n/a