Series:

Wiley Finance

1 primary work • 3 total works

Book 767

Cover of Mathematics and Statistics for Financial Risk Management
Mathematics and Statistics for Financial Risk Management is a practical guide to modern financial risk management for both practitioners and academics. The recent financial crisis and its impact on the broader economy underscore the importance of financial risk management in today's world. At the same time, financial products and investment strategies are becoming increasingly complex. Today, it is more important than ever that risk managers possess a sound understanding of mathematics and statistics. In a concise and easy-to-read style, each chapter of this book introduces a different topic in mathematics or statistics. As different techniques are introduced, sample problems and application sections demonstrate how these techniques can be applied to actual risk management problems. Exercises at the end of each chapter and the accompanying solutions at the end of the book allow readers to practice the techniques they are learning and monitor their progress. A companion website includes interactive Excel spreadsheet examples and templates. This comprehensive resource covers basic statistical concepts from volatility and Bayes' Law to regression analysis and hypothesis testing.
Widely used risk models, including Value-at-Risk, factor analysis, Monte Carlo simulations, and stress testing are also explored. A chapter on time series analysis introduces interest rate modeling, GARCH, and jump-diffusion models. Bond pricing, portfolio credit risk, optimal hedging, and many other financial risk topics are covered as well. If you're looking for a book that will help you understand the mathematics and statistics of financial risk management, look no further.

Cover of Quantitative Financial Risk Management

A mathematical guide to measuring and managing financial risk.     

Our modern economy depends on financial markets. Yet financial markets continue to grow in size and complexity. As a result, the management of financial risk has never been more important.

Quantitative Financial Risk Management introduces students and risk professionals to financial risk management with an emphasis on financial models and mathematical techniques. Each chapter provides numerous sample problems and end of chapter questions. The book provides clear examples of how these models are used in practice and encourages readers to think about the limits and appropriate use of financial models.

Topics include:

•    Value at risk
•    Stress testing
•    Credit risk
•    Liquidity risk
•    Factor analysis
•    Expected shortfall
•    Copulas
•    Extreme value theory
•    Risk model backtesting
•    Bayesian analysis
•     . . . and much more

Cover of The Volatility Smile

The Volatility Smile

The Black-Scholes-Merton option model was the greatest innovation of 20th century finance, and remains the most widely applied theory in all of finance. Despite this success, the model is fundamentally at odds with the observed behavior of option markets: a graph of implied volatilities against strike will typically display a curve or skew, which practitioners refer to as the smile, and which the model cannot explain. Option valuation is not a solved problem, and the past forty years have witnessed an abundance of new models that try to reconcile theory with markets.

The Volatility Smile presents a unified treatment of the Black-Scholes-Merton model and the more advanced models that have replaced it. It is also a book about the principles of financial valuation and how to apply them. Celebrated author and quant Emanuel Derman and Michael B. Miller explain not just the mathematics but the ideas behind the models. By examining the foundations, the implementation, and the pros and cons of various models, and by carefully exploring their derivations and their assumptions, readers will learn not only how to handle the volatility smile but how to evaluate and build their own financial models.

Topics covered include:

  • The principles of valuation
  • Static and dynamic replication
  • The Black-Scholes-Merton model
  • Hedging strategies
  • Transaction costs
  • The behavior of the volatility smile
  • Implied distributions
  • Local volatility models
  • Stochastic volatility models
  • Jump-diffusion models

The first half of the book, Chapters 1 through 13, can serve as a standalone textbook for a course on option valuation and the Black-Scholes-Merton model, presenting the principles of financial modeling, several derivations of the model, and a detailed discussion of how it is used in practice. The second half focuses on the behavior of the volatility smile, and, in conjunction with the first half, can be used for as the basis for a more advanced course.