Risk Assessment and Financial Regulation in Emerging Markets' Banking: Trends and Prospects: Advanced Studies in Emerging Markets Finance
Editat de Alexander M. Karminsky, Paolo Emilio Mistrulli, Mikhail I. Stolbov, Yong Shien Limba Engleză Paperback – 13 mai 2022
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Specificații
ISBN-13: 9783030697501
ISBN-10: 3030697509
Ilustrații: XIV, 396 p. 69 illus., 4 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.58 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Advanced Studies in Emerging Markets Finance
Locul publicării:Cham, Switzerland
ISBN-10: 3030697509
Ilustrații: XIV, 396 p. 69 illus., 4 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.58 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Advanced Studies in Emerging Markets Finance
Locul publicării:Cham, Switzerland
Cuprins
Part I: Banks in Emerging Markets.- Peculiarities and Trends of Banking Systems Development.- Regulation of Financial Risks in Emerging Markets: Past, Present and Future.- Part II: Ratings and Risk Measuring.- Principles of Rating Estimation in Emerging Countries.- Aggregation of Rating Systems for Emerging Financial Markets.- Part III: Estimating and Modeling Credit and Market Risks in Banking.- Bank Credit Risk Modeling in Emerging Capital Markets.- Loss Given Default Estimations in Emerging Capital Markets .- Comparing Bankruptcy Prediction Models in Emerging Markets.- Measures and Assessment of ALM-Risks in Banks: Case of Russia.- Forecasting and Back-Testing of Market Risks in Emerging Markets.- Integrated Risk Measurement System in Commercial Bank.- Economic Capital Structure and Banking Financial Risks Aggregation.- Part IV: Systemic Risks Modeling and Stress Testing.- Exploring the Interplay between Early Warning Systems’ Usefulness and Basel III Regulation.- Does Only Volume Matter? A Stress-test for the Adequacy of International Currency Reserves for Russia.- Regulatory Measures Against Systemic Risk in Banking Sector: The Evidence for the Republic of Belarus.- Real Effects of Financial Shocks in Russia.- Part V: Estimating and Managing Financial Risks: Actual Trends in Emerging Capital Markets.- Innovation in Developing Countries Risk Estimation and Management.- Dynamic Fractal Asset Pricing Model for Financial Risk Evaluation.- Network Effects in Retail Payments Market: Evidence From Individuals.- Conclusion: Instruments of Financial Sustainability in Emerging Markets.
Notă biografică
Alexander M. Karminsky is a trained mathematician and Doctor of Economics and Technics. After 25 years in the banking sector, Dr. Karminsky is currently employed as Professor of Finance and Head of the Research Center of Banking and Risks at the National Research University Higher School of Economics, Moscow (HSE). Alexander Karminsky is on the editorial boards of several scientific journals in Russia and abroad. He is the author of 30+ books and 200+ articles on banking, risk management, econometrics as well as on operational research, IT and controlling.
Paolo Emilio Mistrulli, PhD, is principal economist at the Bank of Italy. He works on various themes related to empirical banking and has a number of papers published in leading international peer-reviewed journals, including the Review of Financial Studies, Journal of Financial Stability, Journal of Banking & Finance, etc.
Professor Mikhail I. Stolbov chairs the Department of Applied Economics at MoscowState Institute of International Relations (MGIMO University). His research focuses on macrofinancial issues, including global financial stability, finance-growth nexus, financial innovations. He has authored a number of studies published in international refereed journals, such as International Economics, Annals of Finance, Empirical Economics, etc.
Paolo Emilio Mistrulli, PhD, is principal economist at the Bank of Italy. He works on various themes related to empirical banking and has a number of papers published in leading international peer-reviewed journals, including the Review of Financial Studies, Journal of Financial Stability, Journal of Banking & Finance, etc.
Professor Mikhail I. Stolbov chairs the Department of Applied Economics at MoscowState Institute of International Relations (MGIMO University). His research focuses on macrofinancial issues, including global financial stability, finance-growth nexus, financial innovations. He has authored a number of studies published in international refereed journals, such as International Economics, Annals of Finance, Empirical Economics, etc.
Yong Shi is Professor and the Executive Deputy Director, Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science and a professor of Information Technology, College of Information Science and Technology, Peter Kiewit Institute, University of Nebraska. He has published more than 15 books and over 200 papers in numerous MCDM-related journals and conference proceedings.
Textul de pe ultima copertă
This book describes various approaches in modelling financial risks and compiling ratings. Focusing on emerging markets, it illustrates how risk assessment is performed and analyses the use of machine learning methods for financial risk assessment and measurement. It not only offers readers insights into the differences between emerging and developed markets, but also helps them understand the development of risk management approaches for banks. Highlighting current problems connected with the evaluation and modelling of financial risks in the banking sector of emerging markets, the book presents the methodologies applied to credit and market financial risks and integrated and payment risks, and discusses the outcomes. In addition it explores the systemic risks and innovations in banking and risk management by analyzing the features of risk measurement in emerging countries. Lastly, it demonstrates the aggregation of approaches to financial risk for emerging financial markets, comparing the experiences of various countries, including Russia, Belarus, China and Brazil.
Caracteristici
Discusses current issues in financial modelling and risk assessment Introduces machine learning methods to evaluate financial risk Includes case studies on China, Russia and Brazil