Quantitative Methods in Derivatives Pricing: An Introduction to Computational FinanceThis book presents a cogent description of the main methodologies used in derivatives pricing. Starting with a summary of the elements of Stochastic Calculus, Quantitative Methods in Derivatives Pricing develops the fundamental tools of financial engineering, such as scenario generation, simulation for European instruments, simulation for American instruments, and finite differences in an intuitive and practical manner, with an abundance of practical examples and case studies. Intended primarily as an introductory graduate textbook in computational finance, this book will also serve as a reference for practitioners seeking basic information on alternative pricing methodologies. Domingo Tavella is President of Octanti Associates, a consulting firm in risk management and financial systems design. He is the founder and chief editor of the Journal of Computational Finance and has pioneered the application of advanced numerical techniques in pricing and risk analysis in the financial and insurance industries. Tavella coauthored Pricing Financial Instruments: The Finite Difference Method. He holds a PhD in aeronautical engineering from Stanford University and an MBA in finance from the University of California at Berkeley. |
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Contents
CHAPTER 1 Arbitrage and Pricing | 1 |
CHAPTER 2 Fundamentals of Stochastic Calculus | 9 |
CHAPTER 3 Pricing in Continuous Time | 41 |
CHAPTER 4 Scenario Generation | 77 |
CHAPTER 5 European Pricing with Simulation | 121 |
Other editions - View all
Quantitative Methods in Derivatives Pricing: An Introduction to ... Domingo Tavella No preview available - 2003 |
Common terms and phrases
accuracy algorithm analytical approach approximate arbitrage Asian option assume barrier option basis functions Bermudan Brownian bridge Chapter computational consider construct control variate convergence correlation covariance default define dimensionality discretely sampled discretization error discretization matrix discuss displacement shock distribution dividend drift early exercise eigenvalues estimator Euler scheme example exercise boundary Exercise opportunities exercise strategy FIGURE finite difference Girsanov theorem grid points implementation importance sampling instrument iterative Ito integral Ito’s lemma jump linear log-normal process LSMC martingale maturity means method money market account moneyness multidimensional normalizing asset number of dimensions one-dimensional Option value path dependency portfolio pricing equation probability density problem quasi-random sequences random variables Replacing result risk neutral risk neutral measure sampling points scenarios simple simulation Sobol solution solve solvers space standard normal stochastic differential equation stochastic process stock price Tavella and Randall techniques tion trajectories transformation trees underlying process variance vector volatility Wiener process
References to this book
A Course in Derivative Securities: Introduction to Theory and Computation Kerry Back No preview available - 2005 |