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Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical methods. It addresses key computational methods in finance, including transform techniques, the finite difference method, and Monte Carlo simulation. Developed from his courses at Columbia University and the Courant Institute of New York University, the author also covers model calibration and optimization and describes techniques, such as Kalman and particle filters, for parameter estimation.
Helping readers accurately price a vast array of derivatives, this self-contained text explains how to solve complex functional equations through numerical meth
Many mathematical assumptions on which classical derivative pricing methods are based have come under scrutiny in recent years. The present volume offers an int
This book discusses the state-of-the-art and open problems in computational finance. It presents a collection of research outcomes and reviews of the work from
Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised
The disciplines of financial engineering and numerical computation differ greatly, however computational methods are used in a number of ways across the field o
