Financial Statements-Based Bank Risk Aggregation

This book proposes a bank risk aggregation framework based on financial statements. Specifically, bank risk aggregation is of great importance to maintain stable operation of banking industry and prevent financial crisis. A major obstacle to bank risk management is the problem of data shortage, which makes many quantitative risk aggregation approaches typically fail. Recently, to overcome the problem of inaccurate total risk results caused by the shortage of risk data, some researchers have proposed a series of financial statements-based bank risk aggregation approaches. However, the existing studies have drawbacks of low frequency and time lag of financial statements data and usually ignore off-balance sheet business risk in bank risk aggregation. Thus, by reviewing the research progress in bank risk aggregation based on financial statements and improving the drawbacks of existing methods, this book proposes a bank risk aggregation framework based on financial statements. It makes full use of information recorded in financial statements, including income statement, on- and off-balance sheet assets, and textual risk disclosures, which solves the problem of data shortage in bank risk aggregation to some extent and improves the reliability and rationality of bank risk aggregation results. This book not only improves the theoretical studies of bank risk aggregation, but also provides an important support for the capital allocation of the banking industry in practice. Thus, this book has theoretical and practical importance for bank managers and researchers of bank risk management.

Proposes a framework of bank risk aggregation based on financial statements Makes full use of information from income statement, on- and off-balance sheet assets, and textual risk disclosures Presents feasible methods to solve the drawbacks of low frequency and time lags of financial statements data

Auteur

Jianping Li is a distinguished professor at the University of Chinese Academy of Sciences (UCAS). He is also the executive vice dean of the School of Economics and Management at the UCAS and the executive member and secretary-general of the International Academy on Information Technology and Quantitative Management (IAITQM). His research interests include risk management and big data analysis. He has published more than 160 papers and 6 monographs. He has been awarded "2020 Elsevier Highly Cited Chinese Researchers", "China Youth Science and Technology Award", "National Outstanding Science and Technology Worker of China", "Excellent Tutor Award of Chinese Academy of Sciences", and won 2 first prizes and 4 second prizes of provincial and ministerial Natural Science/Technology Progress Awards in China.
Lu Wei is Assistant Professor in School of Management Science and Engineering, Central University of Finance and Economics. She received B.S. from Shandong University in 2014 and Ph.D. in management science from University of Chinese Academy of Sciences in 2019. Her research interests focus on bank risk management and text mining. She has published many papers in important journals, including Energy Economics, Accounting & Finance, The North American Journal of Economics and Finance, Review of Quantitative Finance & Accounting, Journal of Risk, Finance Research Letters, and so on. And one of them is the highly cited paper of ESI. She has won the president's special award of the Chinese Academy of Sciences (CAS) during her Ph.D. period, which is the most valuable award for postgraduates of CAS. It specially rewards postgraduates who have made important academic value, made important innovations in theory, or made great breakthroughs in technology.
Xiaoqian Zhu is an associate professor in the School of Economics and Management, University of Chinese Academy of Sciences. She is also the editor of the Journal of International Financial Management & Accounting and the associate editor of the Journal of Operational Risk. She received her Ph.D. in Management Science from the University of Chinese Academy of Sciences in 2015, and a B.S. from the University of Science and Technology of China in 2010. Her research interests focus on financial risk management and big data analysis. She has published over 50 papers in international journals and conferences, including the Innovation, Review of Quantitative Finance and Accounting, Quantitative Finance, International Review of Financial Analysis, Accounting & Finance, Journal of Risk, and a short article published in Nature.

Contenu
Chapter 1. Basic concepts of bank risk aggregation.- Chapter 2. Research review of bank risk aggregation.- Chapter 3. Financial statements based bank risk aggregation framework.- Chapter 4. Bank risk aggregation based on income statement.- Chapter 5. A factor-integral approach to solve the low-frequency problem of income statement data.- Chapter 6. A two-stage bank risk aggregation approach based on financial statements data and external loss data.- Chapter 7. Bank risk aggregation based on income statement and balance sheet.- Chapter 8. Bank risk aggregation with off-balance sheet (OBS) items.- Chapter 9. Analysis of textual risk factors disclosed in financial statements.- Chapter 10. Bank risk aggregation with forwardlooking textual risk disclosures.- Chapter 11. Main conclusions and future research.