0.1 What We’re About
A watershed in the history of value-at-risk (VaR) was the publication of J.P. Morgan’s RiskMetrics Technical Document. Writing in the third edition of that document, Guldimann (1995) went beyond explaining RiskMetrics and described certain alternative “methods” for calculating value-at-risk. Authors of magazine articles, research papers and software marketing materials similarly described how value-at-risk might be calculated using various “methods”. Early “methods” abounded, and they were given an assortment of names. But authors soon winnowed the list to three practical “methods” in widespread use:
- the parametric method,
- the historical simulation method, and
- the structured Monte Carlo method.
Describitng three “methods” for calculating value-at-risk is simple, intuitive and direct. Only one truly new “method” has been introduced since 1995. This might be termed the “quadratic method.” Rouvinez (1997) ultimately published it.
For some time, I felt the top-down “methods” approach for explaining value-at-risk was flawed. Suppose pioneers of aviation had settled on describing three “methods” for building airplanes:
- the monoplane method,
- the biplane method, and
- the triplane method.
That would have missed so much. What about different engine technologies? What about different construction materials? What about so many other features, such as retractable landing gear, pressurized cabins, swept-back wings, fly-by-wire, etc.?
Top-down explanations—such as the “methods” approaches for explaining value-at-risk or aircraft design—are appealing because they go directly to results, but they lead nowhere after that. They inevitably narrow discussion. By comparison, bottom-up explanations build a foundation for deep understanding and further research. I felt that value-at-risk long ago outgrew the top-down “methods” approach of explanation. I wrote this book to provide a flexible bottom-up explanation of value-at-risk.
And I had a second goal for the book: I wanted it to be the first advanced text on value-at-risk, suitable for quantitative professionals.
The book has its origins in 1997, when I first put pen to paper. It took six years to write the first edition, but it achieved my two goals. It described from the bottom up how to design scalable production value-at-risk measures for real trading organizations. Practical, detailed examples were drawn from markets around the world, such as Euro deposits, Pacific Basin equities, physical coffees, and North American natural gas. Sophisticated techniques were presented in book form for the first time, including variance reduction for Monte Carlo value-at-risk measures, quadratic (so-called “delta-gamma”) methods for nonlinear portfolios, and essential remapping techniques. Real-world challenges relating to market data, portfolio mappings, multicollinearity, and intra-horizon events were addressed in detail. Exercises reinforced concepts and walked readers step-by-step through sophisticated computations. For practitioners, researchers, and students, the first edition was an authoritative guide to implementing real-world value-at-risk measures.