财务风险与派生定价理论：从统计物理学到风险管理（英文）

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

By Jean-Philippe Bouchaud, Marc Potters

Publisher:  Cambridge University Press
Number Of Pages:  400
Publication Date:  2004-02-02
ISBN / ASIN:  0521819164
Binding:  Hardcover

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Book Description:

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.

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Date: 2006-10-16  Rating: 3
Review:
Five stars for the intended audience, two stars for the likely holder

Five stars for the intended audience, two stars for the likely holder (a theoretical approximation of the mathfin reader utility curve) give a three star average. Why? Practical utility skew is the operative third moment.

If you have no idea about what I just wrote, this book is not for you. If you do and it made you smile, keep reading.

In Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management authors Bouchaud and Potters place an additional veneer on their previous edition titled Theory of Financial Risks: From Statistical Physics to Risk Management, adding the sexy \"Derivative Pricing\" no doubt in a forgivable attempt to increase sales in this Googlfied world. But this is their failure. While the original edition was a fine, even respectable voice on bridging the knowledge of the intended audience of physicists-turned financial quant, this edition fails on the over covered subject of derivative pricing simply because it is not theoretical, but an empirical and technical review of historical data sets and assumptions and pricing techniques with critiques of the observed differences between theory and empirical results. Needless to say, this fails the smell test in physics, but in finance is as common as Shinola.

Sorry, but critiques of B-S assumptions and better curve fitting is technical, not theoretical. In other words, the theory of why third and fourth moments (skew and kurtosis) become operative and currently present arbitrage opportunities or risk management concerns is not adequately addressed, merely observed, expressed, and called attention to. Moreover, third and fourth moments are approached from a formulaic perspective intended primarily for risk managers and those seeking to make a buck (such as the authors themselves) and have only dangers emphasized. So formulas and expression yes, pure theory no.

Other reviewers have complained about a thematic Gauss-Levy versus Bachelier tone. Ho hum. For the day to day market maker (readers of Baird) such arguments pale in comparison to managing simply the delta of your book. For the physicist, the ghastly collection of noise and spikes that passes for a data set in finance will likely simply better be explained by long periods of madness followed by fleeting moments of clarity than any Procrustean attempt at better curve fitting informed for the empirical work of observing the data signals of a star's decay. Perhaps the only person Bouchaud and Potters's theoretical practical bridge tweaking would have assistance for would be the risk manager of the completely non-correlated short duration portion of the balance sheet of an international bank. Who also happened to be very powerful and have actual accurate real-time data and could implement these ideas. Scale? North of 8 billion before this is useful. Yep, in such a theta world Bachelier's technique rules. But we don't live in such a world yet, although risk managers everywhere delude themselves that they do, often armed with the likes of this book.

Let me hasten to add that Theory is not a bad thing, but its utility best serves the finmath community when it is clearly and explicitly so, without attempting techne and erte. This book is a forgivable beast with two backs, strongly skewed to a good critique of Theory and with fat tails of empiricism, and a bad attempt to be practical. This work therefore, again forgivably, is bound to disappoint practitioners. Joshi is your better bet.

Who is this book not for? Readers and users of Baird, Joshi and Hull and coding front-line quants and risk managers who live in a world of imperfect and delayed data sets will likely find this pointless academic obfuscation. Whom is this book for? I'm a finance guy, not a physicist, and so I read this book in a cyber book group with a theoretical physicist friend. He characterized the book as easy reading for him, but with little new to add that wasn't already known by the reasonably informed physicist turned finquant. His take was that it was a painfully obvious work, curiously passed off as original thinking when in reality it was simply a useful synthesis of common, though specialized knowledge. My take was it was tough sledding to get to obvious conclusions that anyone who has ever run an options book knows through painful experience or wise counsel. Elegantly expressed at a high level for a well-educated readership, but not exactly a holy grail. In other words, the juice wasn't worth the squeeze.

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