Basic statistics for risk management in banks and financial institutions

Table of content:
1:Introduction to Risk Management: Basics of Statistics
2:Descriptive Statistics for Measurement of Risk
3:Probability and Distribution Theorems and Their Applications in Risk Management
4:Hypotheses Testing in Banking Risk Analysis
5:Matrix Algebra and Their Application in Risk Prediction and Risk Monitoring
6:Correlation Theorem and Portfolio Management Techniques
7:Multivariate Analysis to Understand Functional Relationship and Scenario Building
8:Monte Carlo Simulation Techniques and Value a Risk (VaR)
9:Statistical Tools for Model Validation and Back-testing
10:Time Series Forecasting Techniques for Banking Variables
Appendix: Statistical Tables
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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.
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