Ebook: Basic Statistics for Risk Management in Banks and Financial Institutions
Author: Arindam Bandyopadhyay
- Genre: Mathematics // Probability
- Tags: Statistics, Risk Management, Banks, Financial Institutions, Hypotheses Testing, Probability, Distribution Theorems, Matrix Algebra, Multivariate Analysis, Monte Carlo Simulation Techniques, Statistical Tools, Time-Series Forecasting Techniques
- Year: 2022
- Publisher: Oxford University Press
- Edition: 1
- Language: English
- pdf
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.
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.
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