金融市場統(tǒng)計力學(xué)

前言

The present third edition of the statistical mechanics of financial markets is published only four years after the first edition. the success of the book highlights the interest in a summary of the broad research activities on the application of statistical physics to financial markets. i am very grateful to readers and reviewers for their positive reception and comments. why then prepare a new edition instead of only reprinting and correcting the second edition?The new edition has been significantly expanded, giving it a more prac-tical twist towards banking. the most important extensions are due to my practical experience as a risk manager in the german savings banks' asso-ciation (dsgv): two new chapters on risk management and on the closely related topic of economic and regulatory capital for financial institutions, re-spectively, have been added. the chapter on risk management contains both the basics as well as advanced topics, e.g. coherent risk measures, which have not yet reached the statistical physics community interested in financial mar-kets.

內(nèi)容概要

　　The present third edition of the statistical mechanics of financial markets is published only four years after the first edition. the success of the book highlights the interest in a summary of the broad research activities on the application of statistical physics to financial markets. i am very grateful to readers and reviewers for their positive reception and comments. why then prepare a new edition instead of only reprinting and correcting the second edition?

作者簡介

作者：（德國）沃伊特（J.Voit）

書籍目錄

1.introduction1.1 motivation1.2 why physicists? why models of physics?1.3 physics and finance - historical1.4 aims of this book2.basic information on capital markets2.1 risk2.2 assets2.3 three important derivatives2.4 derivative positions2.5 market actors2.6 price formation at organized exchanges3.random walks in finance and physics3.1 important questions3.2 bachelier's "theorie de la speculation"3.3 einstein's theory of brownian motion3.4 experimental situation4.the black-scholes theory of option prices4.1 important questions4.2 assumptions and notation4.3 prices for derivatives4.4 modeling fluctuations of financial assets4.5 option pricing5.scaling in financial data and in physics5.1 important questions5.2 stationarity of financial markets5.3 geometric brownian motion5.4 pareto laws and levy flights5.5 scaling, levy distributions,and levy flights in nature5.6 new developments: non-stable scaling, temporal and interasset correlations in financial markets6.Turbulence and Foreign Exchange Markets6.1 Important Questions6.2 Turbulent Flows6.2.1 Phenomenology6.2.2 Statistical Description of Turbulence6.2.3 Relation to Non.extensive Statistical Mechanics6.3 F0reign Exchange Markets6.3.1 Why Foreign Exchange Markets?6.3.2 Empirical Resu：Its6.3.3 Stochastic Cascade Models6.3.4 The Multifractal Interpretation7.Derivative Pricing Beyond Black-Scholes7.1 Important Questions7.2 An Integral namework for Derivative Pricing7.3 Application to Forward Contracts7.4 Option Pricing(European Calls)7.5 Monte Carlo Simulations7.6 Option Pricing in a Tsallis world7.7 Path Integrals：Integrating the Fat Tails into Option Pricing7.8 Path Integrals：Integrating Path Dependence into Option Pricing8.Microscoplc Market MOdeIs8.1 Important Questions8.2 Are Markets Eflicient?8.3 Computer Simulation of Market Models8.3.1 Two Classical Examples8.3.2 Recent Models8.4 The Minority Game8.4.1 The Basic Minority Game8.4.2 A Phase Transition in the Minority Game8.4.3 Relation to Financial Markets8.4.4 Spin Glasses and an Exact Solution8.4.5 Extensions ofthe Minority Game9.Theory of Stock Exchange Crashes9.1 Important Questions9.2 Examples9.3 Earthquakes and MateriaI Failure9.4 Stock Exchange Crashes9.5 What Cause8 Crashes?9.6 Are Crashes Rational?9.7 What Happens After a Crash?.，9.8 A Richter Scale for Financial Markets10.R.isk Management10.1 Important Questions10.2 What is Risk?10.3 Measures of Risk10.3.1 Volatility10.3.2 Generalizations of Volatility mad Moments10.3.3 Statistics of Extremal Events10.3.4 V_alue at Risk10.3.5 Coherent Measures of Risk10.3.6 Expected Shortfall10.4 Types of Risk10.4.1 Market Risk10.4.2 Credit Risk10.4.3 0perational msk10.4.4 Liquiditv msk10.5 msk Management10.5.1 Risk Management Requires a Strategy10.5.2 Limit Systems10.5.3 Hedging10.5.4 Portfolio Insurance10.5.5 Diversification10.5.6 Strategic msk Management11.Economic and Regulatory Capital for Financial Institutions11.1 Important Questions11.2 Economic Capital11.2.1 What Determines Economic Capital?11.2.2 How Calculate Economic Capital?11.2.3 How Allocate Economic Capital?11.2.4 Economic Capital a Management Tool11.3 The Regulatory Framework11.3.1 Why Banking Regulation?11.3.2 Risk-Based Capital Requirements11.3.3 Basel I：Regulation of Credit Risk11.3.4 Internal Models11.3.5 Basel II：The New International Capital Adequacy Framework11.3.6 0utlook：Basel IIl and Babel IVAppendixNotes and RaferencesIndex

章節(jié)摘錄

插圖：When attempting to draw parallels between statistical physics and finan-cial markets, an important source of concern is the complexity of humanbehavior which is at the origin of the individual trades. Notice, however, that nowadays a significant fraction of the trading on many markets is performed by computer programs, and no longer by human operators. Furthermore, if we make abstraction of the trading volume, an operator only has the possi-bility to buy or to sell, or to stay out of the market. Parallels to the Ising or Potts models of Statistical Physics resurface!More specifically, take the example of Fig. 1.1. If we subtract out long-term trends, we are left essentially with some kind of random walk. In other words, the evolution of the DAX index looks like a random walk to which is superposed a slow drift. This idea is also illustrated in the following story taken from the popular book "A Random Walk down Wall Street" by B. G. Malkiel [3], a professor of economics at Princeton. He asked his students to derive a chart from coin tossing.

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