Parallels between physics and finance were established in a 100-year-long interaction of both disciplines. This study examines these parallels as well as research results on capital markets by statistical physics. The random walk, well known in physics, is also the basic model in finance. On this model is built the Black-Scholes theory of option pricing and hedging, or methods of risk control by diversification. The underlying assumptions are discussed using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion. On this basis, new theories of derivative pricing and of risk control can be formulated. Computer simulations of interacting agent models of financial markets provide insight into the origins of asset price fluctuations. Stock exchange crashes can be modelled in analogy to phase transitions and earthquakes. These models allow for predictions.
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From the reviews of the third edition:
"An excellent job of integrating many of the most important themes from econophysics in a relatively small volume. ... The book serves its purpose, as a textbook on econophysics, superbly and one can tell that it developed from a course of lectures. The book is written with extreme clarity and an excellent pedagogical style. For philosophers who wish to acquaint themselves with the field of econophysics (beyond a superficial level), this is the book to invest in." (Dean Rickles, Studies in History and Philosophy of Modern Physics, Vol. 38, 2007)
This highly praised introductory treatment describes the parallels between statistical physics and finance - both those established in the 100-year long interaction between these disciplines, as well as new research results on financial markets.
The random-walk technique, well known in physics, is also the basic model in finance, upon which are built, for example, the Black-Scholes theory of option pricing and hedging, plus methods of portfolio optimization. Here the underlying assumptions are assessed critically. Using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion, the book develops a more accurate description of financial markets based on random walks. With this approach, novel methods for derivative pricing and risk management can be formulated. Computer simulations of interacting-agent models provide insight into the mechanisms underlying unconventional price dynamics. It is shown that stock exchange crashes can be modelled in ways analogous to phase transitions and earthquakes, and sometimes have even been predicted successfully.
This third edition of The Statistical Mechanics of Financial Markets especially stands apart from other treatments because it offers new chapters containing a practitioner's treatment of two important current topics in banking: the basic notions and tools of risk management and capital requirements for financial institutions, including an overview of the new Basel II capital framework which may well set the risk management standards in scores of countries for years to come.
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