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The book provides an engaging account of theoretical, empirical, and practical aspects of various statistical methods in measuring risks of financial institutions, especially banks. In this book, the author demonstrates how banks can apply many simple but effective statistical techniques to analyze risks they face in business and safeguard themselves from potential vulnerability. It covers three primary areas of banking; risks-credit, market, and operational risk and in a uniquely intuitive, step-by-step manner the author provides hands-on details on the primary statistical tools that can be applied for financial risk measurement and management. The book lucidly introduces concepts of various well-known statistical methods such as correlations, regression, matrix approach, probability and distribution theorem, hypothesis testing, value at risk, and Monte Carlo simulation techniques and provides a hands-on estimation and interpretation of these tests in measuring risks of the financial institutions. The book strikes a fine balance between concepts and mathematics to tell a rich story of thoughtful use of statistical methods.
How can financial institutions effectively utilize statistical methodologies to identify, measure, and mitigate credit, market, and operational risks? Arindam Bandyopadhyay leverages his expertise in banking and quantitative analysis to bridge the gap between abstract statistical theory and practical application. The text provides a structured framework for risk assessment, utilizing empirical data and mathematical models to demonstrate how banks can safeguard their operations against financial volatility.
What You Will Find
Scope Limits
Experts identify this work as a practical resource for professionals seeking to apply statistical rigor to banking risk management. Readers frequently note the balance between conceptual clarity and mathematical application, making it a useful reference for those transitioning from theory to institutional practice.
Page Count:
376
Publication Date:
2022-01-01
Publisher:
OUP Oxford
ISBN-10:
0192665499
ISBN-13:
9780192665492
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