Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk ManagementRisk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets. Summarising theoretical developments in the field, this 2003 second edition has been substantially expanded. Additional chapters now cover stochastic processes, Monte-Carlo methods, Black-Scholes theory, the theory of the yield curve, and Minority Game. There are discussions on aspects of data analysis, financial products, non-linear correlations, and herding, feedback and agent based models. This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies. |
Contents
1 | |
17 | |
Continuous time limit Ito calculus and path integrals | 43 |
Analysis of empirical data | 55 |
Financial products and financial markets | 69 |
basic results | 87 |
Nonlinear correlations and volatility fluctuations | 107 |
Skewness and pricevolatility correlations | 130 |
fundamental concepts | 226 |
kurtosis | 242 |
hedging and residual risk | 254 |
the role of drift and correlations | 276 |
the Black and Scholes model | 290 |
some more specific problems | 300 |
minimum variance MonteCarlo | 317 |
The yield curve | 334 |
Crosscorrelations | 145 |
Risk measures | 168 |
Extreme correlations and variety | 186 |
Optima portfolios | 202 |
Simple mechanisms for anomalous price statistics | 355 |
372 | |
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Common terms and phrases
A-hedge assume average return behaviour Black-Scholes bond Bouchaud Brownian motion Chapter coefficient compute contract correlation function correlation matrix corresponding cumulants decay defined depends discussed effect eigenvalues empirical equal equation example exponent exponential factor financial markets finds finite formula forward contract Gaussian variables given hedging strategy implied volatility independent interest rate inverse gamma distribution kurtosis leads Levy distribution limit linear log-normal log-normal distribution maturity mean minimization Monte-Carlo negative non-Gaussian non-zero Note obtained optimal hedge optimal portfolio optimal strategy option price parameter pay-off power-law price changes price increments probability distribution Quantitative Finance quantity random matrices random variables random walk residual risk result scale Section simple skewness statistical stochastic volatility Student distribution tail amplitude term theory trading uncorrelated value-at-risk variance variogram Vasicek model volatility correlations volatility fluctuations wealth balance zero