Numerical Methods for Finance
John Miller, David Edelman, John Appleby
CRC Press, Sep 21, 2007 - Business & Economics - 312 pages
Featuring international contributors from both industry and academia, Numerical Methods for Finance explores new and relevant numerical methods for the solution of practical problems in finance. It is one of the few books entirely devoted to numerical methods as applied to the financial field.
Presenting state-of-the-art methods in this area
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1FCIR 1FGV 24 DAX stocks 2FGV 2FV model affine algorithm American options asset benchmark Bermudan Black–Scholes bond prices Brigo Brownian motion Carlo Methods Cauchy distribution chapter CIR model computational condition consider convergence correlation counterparty risk credit risk CRMs defined derivatives detrended dimension discretization dynamics equation error curves evaluation factor FFT-SP Figure financial time series forecast function given Glasserman grid points Hurst coefficient Hurst exponent implied volatility interest rates interest-rate intraday Journal Kalman filter KF GARCH linear log-likelihood martingale Mathematics matrix mean MLCE Monte Carlo method Monte Carlo simulation normal distribution one-factor optimal parameter vectors option prices out-of-sample parameter estimates payoff Pelsser 21 portfolio problem Put Options quantile regression riskless sample scaling law Schrager and Pelsser SDEs self-similar short rate solution standard stochastic volatility strike price swap swaption contracts swaption pricing methodology TABLE term-structure models underlying variables variance Vasicek models zero
Page ii - Portfolio Optimization and Performance Analysis, Jean-Luc Prigent Robust Libor Modelling and Pricing of Derivative Products, John Schoenmakers Structured Credit Portfolio Analysis, Baskets & CDOs, Christian Bluhm and Ludger Overbeck Numerical Methods for Finance, John AD Appleby, David C.