Market Models: A Guide to Financial Data Analysis (Hardcover)

by Carol Alexander (Author) "This chapter introduces some of the concepts that are fundamental to the analysis of volatility and correlation of financial assets..." (more)
Key Phrases: fixed strike deviations, volatility smile surface, strike volatilities, Monte Carlo, Market Models, General Electric (more...)

Editorial Reviews

Product Description
Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander's clear exposition provides valuable insights at every stage.

In each of the 13 Chapters, Market Models presents real world illustrations to motivate theoretical developments. The accompanying CD contains spreadsheets with data and programs; this enables the reader to implement and adapt many of the examples. The pricing of options using normal mixture density functions to model returns; the use of Monte Carlo simulation to calculate the VaR of an options portfolio; modifying the covariance VaR to allow for fat-tailed P&L distributions; the calculation of implied, EWMA and 'historic' volatilities; GARCH volatility term structure forecasting; principal components analysis; and many more are all included.

Market Models: A Guide to Financial Data Analysis is the ideal reference for all those involved in market risk measurement, quantitative trading and investment analysis.

From the Inside Flap
In part 1, Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered in part 2 where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is explained in part 3, with coverage ranging from the application cointegration to long-short equity hedge funds, to high-frequency data prediction using neural networks and nearest neighbour algorithms .

Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self-contained.

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Product Details

• Hardcover: 445 pages
• Publisher: Wiley (November 15, 2001)
• Language: English
• ISBN-10: 0471899755
• ISBN-13: 978-0471899754
• Product Dimensions: 9.9 x 7.7 x 1.2 inches
• Shipping Weight: 3 pounds (View shipping rates and policies)
• Average Customer Review: 4.5 out of 5 stars See all reviews (17 customer reviews)
• Amazon.com Sales Rank: #74,025 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

16 of 16 people found the following review helpful:

5.0 out of 5 stars Worth the money, August 27, 2003

By	N. Banks (Charlotte, NC United States) - See all my reviews (REAL NAME)

If you are looking for detailed rigorous mathematical development then look elsewhere, that is not the reason to purchase this book. It is targeted towards application and there it excels. I have not seen any other book on this topic that so effectively presents a level-headed applied approach that keeps the basic assumptions of the models firmly in sight.
What tool fits when is nicely discussed.

18 of 19 people found the following review helpful:

4.0 out of 5 stars Nice book, June 20, 2003

By	"derivatives_trader" (NY) - See all my reviews

I will consider this book as a good introduction to different ways to analyze market data (covering mainly equity but do touch on fixed income as well as currency). I would emphasize that the book model the market more from an empirical point of view. The author gives a good description of the GARCH model as well as PCA analysis. Being a fixed income derivatives trading, I find both sections particularly useful for real world trading. The risk modeling section should expand into topics other than VAR such as coherent risk measures which are more useful. The co-integration section is a must for any traders who want to trade mean-reversion or stats arbitrage.

Overall, I think that the book covers all basic to intermediate mathematics, econometrics and finance necessary for anyone who wants to model market data. The book explains how to use such model for trading, risk management as well as market data visualization / understanding.

19 of 21 people found the following review helpful:

5.0 out of 5 stars A buy you'll be happy you made., May 25, 2002

By	Guy Kamdem (Reading United Kingdom) - See all my reviews

I'm a student of Carol Alexander at the ISMA Centre. This could set a bias, but I have tried in my review to be as objective as I possibly can.
Having covered with academic rigor 9 out of the 13 chapters of "market models", the only way i could describe it is as an excellent toolbox for financial modelling and a precise application to these tools to Risk measurement.

One of the main features that make this book stand out of the crowd of similar books is the fact that it's paved with illustrations using real market data. You get a feel of the reality, not just some conceptual approach that might or might not work.

The other feature that gives this book a step ahead of others is how Carol managed to make it perfectly accessible to someone with little mathematical weapons, yet kept it absolutely worth for the Quant!

The constant but constructive analysis of the "practical" limitations and advantages of such and such models explained or mentioned, adds to keeping the whole scene of the book very realistic.

It's also a true solutions book; it doesn't just tell you what to do by presenting the theory behind the concept, but how to do it by applying it to real data.

Chapters like "principal components" and ["Non Normal Models" or Normal mixtures" as she likes to call them], bring forward some elegant, yet powerful and straightforward methods for modelling in finance.

Market Models should be a trader's must read and without a doubt, "THE" book of the modern Risk Manager.

Go get the book and learn what you need to know!