Measuring Market Risk with Value at Risk

Providing risk analysts and managers with a step-by-step approach to the estimation of VaR, this book maintains a global view of the subject, encompassing all the most important issues-statistical, financial, and regulatory-that are essential to real-world implementation.

In Measuring Market Risk with Value at Risk, authors Penza and Bansal focus on:

• The reasons for the growing importance of market risk measurement for banks, including an overview of Asset-Liability Management techniques and why they are becoming less effective, tools at controlling and managing risk
  
• The statistical foundations of VaR models covering the concept of returns and ways of calculating asset returns; estimating conditional returns; variance of returns using RiskMetrics and ARCH/GARCH techniques in particular
  
• Techniques for calculating VaR for single instruments including fixed income, equity, and derivative instruments
  
• Analysis of the models-both parametric and simulation-for measuring the Value at Risk in a portfolio, paying particular attention to the limits and drawbacks of the VaR approach and the main weaknesses of the commonly used models.
  

Great attention has been devoted through out the book to the actual implementation of the techniques presented. Case studies using real data are provided to illustrate real-world applications of the methods, making the methodology provided both timely and indispensable for risk managers and students of finance alike.

Contents

• Global Banking Industry.
  
• Risk Management Approaches in BankingActivity.
  
• Financial Risk Management and Regulations.
  
• A Simple Introduction to Value-at-Risk.
  
• Measuring Prices and Returns.
  
• Statistics for Prices and Returns.
  
• Estimating and Forecasting Volatility.
  
• The Distribution of Returns.
  
• Fractal Distributions and Applications to VaR.
  
• Fixed-Income Mapping.
  
• Equity Pricing.
  
• Derivative Pricing.
  
• Calculating VaR: An Overview.
  
• Parametric Normal Models.
  
• Historical Simulation Models.
  
• Monte Carlo Simulation Methods.
  
• Final Remarks: Limits of VaR.
  
• Index.