Introduction to Financial Engineering and Risk Management
Master financial engineering fundamentals including fixed income securities, derivatives pricing, and risk management using advanced mathematical models.
Master financial engineering fundamentals including fixed income securities, derivatives pricing, and risk management using advanced mathematical models.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Financial Engineering and Risk Management Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.6
(231 ratings)
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English
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What you'll learn
Master probability theory and optimization techniques for financial modeling
Understand fixed income securities and their derivative instruments
Learn to price swaps and options using the 1-period Binomial Model
Apply multi-period Binomial and Black-Scholes Models
Analyze term structure of interest rates
Develop skills in derivatives pricing and risk assessment
Skills you'll gain
This course includes:
7.2 Hours PreRecorded video
17 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course provides a fundamental introduction to financial engineering and risk management concepts. Starting with mathematical foundations in probability and optimization, it progresses through fixed income securities, derivatives, and their pricing models. The curriculum covers essential topics including present value computation, term structure of interest rates, swaps, options, and the binomial model. Advanced concepts include multi-period pricing models and the Black-Scholes model, with practical applications in pricing various financial instruments.
Course Overview
Module 1 · 38 Minutes to complete
Pre-Requisite Materials
Module 2 · 5 Hours to complete
Introduction to Basic Fixed Income Securities
Module 3 · 2 Hours to complete
Introduction to Derivative Securities
Module 4 · 4 Hours to complete
Option Pricing in the Multi-Period Binomial Model
Module 5 · 6 Hours to complete
Fee Structure
Instructors
Expert in Optimization and Professor at Columbia University
Dr. Garud N. Iyengar is the Tang Family Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he has been a faculty member since 1998. He also serves as the Avanessians Director of the Data Science Institute (DSI) at Columbia, leading initiatives in education and research for data science. Dr. Iyengar's research interests encompass a variety of topics, including convex optimization, robust optimization, queuing networks, combinatorial optimization, and mathematical finance.He received his Ph.D. and M.S. in Electrical Engineering from Stanford University and his B.Tech from the Indian Institute of Technology (IIT). Dr. Iyengar has published extensively in his field, with over 90 publications and two patents to his name. He has held several leadership roles, including Chair of the Department of Industrial Engineering and Operations Research from 2013 to 2019 and Senior Vice Dean for Research and Academic Programs at Columbia Engineering.Dr. Iyengar teaches several courses on Coursera, such as "Introduction to Financial Engineering and Risk Management" and "Optimization Methods in Asset Management," aimed at equipping students with essential skills in finance and operations research.
Expert in Financial Engineering and Professor at Columbia University
Dr. Ali Hirsa is a Professor of Professional Practice in the Department of Industrial Engineering and Operations Research at Columbia University, where he has been a faculty member since 2017, having previously served as an Adjunct Professor since 2000. He is also the Managing Partner at Sauma Capital, LLC, a New York hedge fund. Dr. Hirsa's expertise lies in financial engineering, with a focus on asset pricing, derivatives, and optimization methods in asset management.He holds a Ph.D. in Applied Mathematics from the University of Maryland at College Park and an MBA with an emphasis on Finance. Dr. Hirsa has extensive industry experience, having held significant positions at firms such as Morgan Stanley and Banc of America Securities, where he developed quantitative trading strategies.Dr. Hirsa teaches several courses on Coursera, including "Introduction to Financial Engineering and Risk Management" and "Advanced Topics in Derivative Pricing." His research interests include algorithmic trading, machine learning, and computational finance, and he has authored multiple publications in these areas.
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4.6 course rating
231 ratings
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