Computational Methods in Finance

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.

Ali Hirsa is a Professor and director of the Center for Artificial Intelligence in Business Analytics and Financial Technology and director of the Financial Engineering Program in the Industrial Engineering & Operations Research Department at Columbia University in the City of New York. He is also Chief Scientific Officer at ASK2.ai and Managing Partner at Sauma Capital, LLC, a New York Hedge Fund. Previously he was a Partner and Head of Analytical Trading Strategy at Caspian Capital Management, LLC. Ali has worked in a variety of quantitative positions at Morgan Stanley, DV Trading, Banc of America Securities, and Prudential Securities. Ali was also a Fellow at Courant Institute of New York University in the Mathematics of Finance Program from 2004 to 2014. Ali is the author of ＂Computational Methods in Finance,＂ Chapman & Hall/CRC 2012, co-author of ＂An Introduction to Mathematics of Financial Derivatives,＂ third edition, Academic Press with Salih Neftci, and the editor-in-chief of the Journal of Investment Strategies. He is a frequent speaker at academic and practitioner conferences. Ali received his Ph.D. in Applied Mathematics from the University of Maryland at College Park under the supervision of Professors Howard C. Elman and Dilip B. Madan.