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Computational Methods in Finance is a book developed from the author's courses at Columbia University and the Courant Institute of New York University. This self-contained text is designed for graduate students in financial engineering and mathematical finance, as well as practitioners in the financial industry. It will help readers accurately price a vast array of derivatives. This new edition has been thoroughly revised throughout to bring it up to date with recent developments. It features numerous new exercises and examples, as well as two entirely new chapters on machine learning.Features Explains how to solve complex functional equations through numerical methods Includes dozens of challenging exercises Suitable as a graduate-level textbook for financial engineering and financial mathematics or as a professional resource for working quants.
This text addresses a variety of numerical methods for pricing derivative contracts, including Fourier techniques, finite differences, numerical simulation, and Monte Carlo simulation methods one of the first books to cover all of these techniques. After presenting the basics of pricing techniques, it covers key concepts of calibration and parameter estimation. Written by a popular professor at Columbia University and NYU 's Courant Institute, the book is suitable for any graduate course on computational finance in financial engineering and financial mathematics programs as well as for practitioners interested in computational methods in finance.
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