Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management [Hardcover]

Jean-Philippe Bouchaud (Author), Marc Potters (Author)

Book Description

Publication Date: February 2, 2004 | ISBN-10: 0521819164 | ISBN-13: 978-0521819169 | Edition: 2

Summarizing market data developments, some inspired by statistical physics, this book explains how to better predict the actual behavior of financial markets with respect to asset allocation, derivative pricing and hedging, and risk control. Risk control and derivative pricing are major concerns to financial institutions. The need for adequate statistical tools to measure and anticipate amplitude of potential moves of financial markets is clearly expressed, in particular for derivative markets. Classical theories, however, are based on assumptions leading to systematic (sometimes dramatic) underestimation of risks.

Editorial Reviews

Review

"...thought-provoking...The feeling one is left with after putting the book down is one of time well spent."
Risk

"...the authors offer fresh and valuable insights into financial markets." -
Mathematical Reviews

"The book is well written and self-contained...recommended to anyone interested in a new and fresh approach to the dynamics of financial markets."
Journal of Statistical Physics

"The book is interesting not only for physicists working in finance, but also practicioners and scholars with a mathematical or statistical background."
Journal of the American Statistical Association

Book Description

Risk control and derivative pricing are major concerns to financial institutions. The need for adequate statistical tools to measure and anticipate amplitude of potential moves of financial markets is clearly expressed, in particular for derivative markets. Classical theories, however, are based on assumptions leading to systematic (sometimes dramatic) underestimation of risks. Theory of Financial Risk and Derivative Pricing summarises developments, some inspired by statistical physics, using which one can take into account more faithfully the real behaviour of financial markets for asset allocation, derivative pricing and hedging, and risk control.

See all Editorial Reviews

Product Details

• Hardcover: 400 pages
• Publisher: Cambridge University Press; 2 edition (February 2, 2004)
• Language: English
• ISBN-10: 0521819164
• ISBN-13: 978-0521819169
• Product Dimensions: 9.8 x 7 x 1 inches
• Shipping Weight: 2.1 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (8 customer reviews)
• Amazon Best Sellers Rank: #1,365,851 in Books (See Top 100 in Books)

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19 of 22 people found the following review helpful:

5.0 out of 5 stars Summarises new advances in quantifying financial risk, September 19, 2000

By 

Dr Craig Mounfield - See all my reviews

This review is from: Theory of Financial Risks: From Statistical Physics to Risk Management (Hardcover)

`Econophysics' (the application of techniques developed in the physical sciences to economic, business and financial problems) has emerged as a newly active field of interdisciplinary research. `Theory of Financial Risks' (written by two of the pioneers of this field) highlights very clearly the contribution that physicists can make to quantitative finance.

From the outset the point of view of the book is one of empirical observation (of the statistical properties of asset price dynamics) followed by the development of theories attempting to explain these results and enabling quantitative predictions to be made. This philosophy is reflected in the structure of the book. After a brief account of relevant mathematical concepts from probability theory the statistics of empirical financial data is analysed in detail. A key result from this analysis is the observation that the correlation matrix (measuring the correlation in asset price movements between pairs of assets) is dominated by measurement noise (which, as the authors observe, has serious consequences for the construction of optimal portfolios). Chapter 3 begins the core theme of the book with a discussion of measures of risk and the construction of optimal portfolios. A central result of this chapter is that minimisation of the variance of a portfolio may actually increase its Value-at-Risk.

The theme of improved measures of risk continues in chapters 4 and 5 which focus on futures and options. A new theory for measuring the risk in derivative pricing is presented. In the appropriate limit (continuous-time, Gaussian statistics) this model reproduces the central results of the Black-Scholes model - namely that one can construct a portfolio of options and assets such that the residual risk is identically equal to zero. However as the book has constantly highlighted, these market conditions are simply not observed in practice. Moreover the new theory presented allows one to calculate the residual risk which exists under more general and realistic market conditions (allowing the development of improved trading strategies).

In summary this book highlights very clearly many of the inadequacies of current financial theories and presents a number of new approaches, based upon concepts developed in statistical physics, to overcome these problems. It is to be recommended to both students of finance as well as to professional analysts as a good example of how an interdisciplinary approach to financial engineering may yield improved measures of risk.

18 of 22 people found the following review helpful:

3.0 out of 5 stars Fat tails and more, June 5, 2002

By 

Professor Joseph L. McCauley "Joseph L. McCauley" (Austria+Texas) - See all my reviews

This review is from: Theory of Financial Risks: From Statistical Physics to Risk Management (Hardcover)

This text has a nice discussion of Levy distributions and (important!) discusses why the central limit theorem does not apply to the tails of a distribution in the limit of many independent random events. An exponential distribution is given as an example how the CLT fails. I was first happy to see a chapter devoted to portfolio selection, but the chapter (like most of the book) is very difficult to follow (I gave up on that chapter, unhappily, because it looked interesting). The notation could have been better (to be quite honest, the notation is horrible), and the arguments (many of which are original) could have been made sharper and clearer. For my taste, too many arguments in the text rely on uncontrolled approximations, with Gaussian results as special limiting cases. The chapters on options are original, introducing their idea of history-dependent strategies (however, to get a strategy other than the delta-hedge does not not require history-dependence, CAPM is an example), but the predictions too often go in the direction of showing how Gaussian returns can be retrieved in some limit (I find this the opposite of convincing!). For an introduction to options, the 1973 Black-Scholes paper is still the best (aside from the wrong claim that CAPM and the delta-hedge yield the same results). The argument in the introduction in favor of 'randomness' as the origin of macroscopic law left me as cold as a cucumber. On page 4 a density is called 'invariant' under change of variable whereas 'scalar' is the correct word (a common error in many texts on relativity). The explanation of Ito calculus is inventive but inadequate (see instead Baxter and Rennie for a correct and readable treatment, one the forms the basis for new research on local volatility). Also, utlility is once mentioned but never criticized. Had the book been more pedagogically written then one could well have used it as an introductory text, given the nice choice of topics discussed.

11 of 13 people found the following review helpful:

5.0 out of 5 stars An Unconventional and Engaging Treatment of Risk, September 15, 2000

By 

Raymond J. Hawkins (San Francisco, CA United States) - See all my reviews

This review is from: Theory of Financial Risks: From Statistical Physics to Risk Management (Hardcover)

In 'More Heat Than Light', Philip Mirowski observed that the expertise brought to economics by the " ... influx of engineers, physicists manqués, and mathematicians during the Great Depression and after ... did not get parlayed into novel physical/economic metaphors." In the literature of the new field of "econophysics" there are promising indications that the recent influx into finance following the end of the cold war will not repeat this. An exciting addition to this literature is the recent publication of this augmented and English version of Théorie des Risques Financiers.

In this monograph Drs. Bouchaud and Potters present much of their research together with related contemporary and previous work including that of Bachelier. Their "physicists viewpoint" of comparing theory to observed data appears early in the first chapter where time-series data illustrating 3 market crashes motivates their review of the basic notions of probability with an emphasis on non-Gaussian probability densities. This is followed by an interesting data-intensive comparison of these notions to the statistics of real prices including, as examples, the S&P 500 index, the DEM/USD exchange rate, and the Bund futures contract. The results of this comparison between theory and observation are then applied in the chapters that follow in which portfolio optimization, risk management, and the valuation of derivative securities are discussed.

The authors' approach in general, and to derivative securities in particular, is both unconventional and refreshing. It will appeal to those who have wondered if stochastic calculus is really required to price options. They demonstrate how a number of well-known results can be recovered in the appropriate (usually Gaussian) limits and provide an even-handed discussion of the risk associated with failing to include non-Gaussian effects.

This book is readily accessible to readers who have/can read either McQuarrie's 'Statistical Mechanics' or Ingersoll's 'Theory of Financial Decision Making'. I enjoyed this book because of the authors' unconventional approach, stat-mech style, interesting comparisons of theory and data, and the important implications of their approach for risk measurement and management