Columbia University
Introduction to Financial Engineering and Risk Management

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Columbia University

Introduction to Financial Engineering and Risk Management

Garud Iyengar
Ali Hirsa
Martin Haugh

Instructors: Garud Iyengar

40,697 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(239 reviews)

Intermediate level

Recommended experience

19 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.6

(239 reviews)

Intermediate level

Recommended experience

19 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

17 assignments

Taught in English

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This course is part of the Financial Engineering and Risk Management Specialization
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There are 5 modules in this course

Welcome to Financial Engineering and Risk Management

What's included

1 video3 readings

Welcome to Week 2! This week, we will cover mathematical foundations that are necessary for the study of future modules. In a nutshell, we will introduce probabilities and optimization. The theory of probability is the mathematical language to characterize uncertainties, e.g. how to describe the chances that the price of a particular stock will go up tomorrow. To make things precise, we need probabilities. Optimization is a set of toolkits that allow us to search for optimal solutions. For example, given a budget constraint, how do we maximize the profit? We need mathematical optimization. Financial engineers apply probabilistic models to capture the regularities of financial products, and apply optimization techniques to optimize their strategies. These mathematical toolkits will serve as a cornerstone for your financial engineering career.

What's included

18 videos6 readings5 assignments

Welcome to Week 3! This week, we officially embark on the journey of financial engineering and risk management. We will start with the fundamentals of financial engineering, i.e. the principles of pricing. In financial markets, given a financial product, how do we calculate its prices? These pricing principles will serve as the cornerstone of our future modules. We will also cover the basics of fixed income instruments, which serve as the building blocks of financial markets. If you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.)

What's included

7 videos2 readings3 assignments

Welcome to Week 4! This week, we will cover a new family of financial products: derivative securities. Derivative securities, as the name suggests, are financial products that derive their value from some underlying assets, such as interest rates or stocks. The prosperity of modern financial markets is due in large part to the wide variety of derivative securities on the markets such as forwards, futures, swaps, and options as we will introduce in this module. We will also introduce the 1-period binomial model, a simplified framework that allows us to calculate the prices of derivative securities. Despite its simplicity, 1-period binomial model is the building block of more powerful pricing models as we will find out in future modules. As always, if you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.)

What's included

11 videos3 readings4 assignments

Welcome to Week 5! This week, we will continue from the last module, and extend from the 1-period binomial model to the multi-period binomial model. Multi-period binomial model is nothing but stacking multiple 1-period binomial models together. We will see how this simple construction allows us to price financial products over long horizons. As an illustrative example, we will price the American options using the multi-period model. Moreover, we will cover more advanced pricing models such as the Black Scholes model. We will see how the Black Scholes model is a natural extension of the multi-period binomial model and is widely applicable in practice. As always, if you get stuck on the quizzes, you should post on the Discussions to ask for help. (And if you finish early, I hope you'll go there to help your fellow classmates as well.)

What's included

10 videos7 readings5 assignments1 discussion prompt

Instructors

Instructor ratings
4.5 (68 ratings)
Garud Iyengar
Columbia University
7 Courses439,772 learners
Ali Hirsa
Columbia University
5 Courses49,703 learners

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