Financial Risk Management with R

Financial Risk Management with R

This course is part of Entrepreneurial Finance: Strategy and Innovation Specialization

Instructor: David Hsieh

19,645 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

259 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

259 reviews

Intermediate level

Some related experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

28 assignments

Taught in English

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This course is part of the Entrepreneurial Finance: Strategy and Innovation Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 4 modules in this course

This course teaches you how to calculate the return of a portfolio of securities as well as quantify the market risk of that portfolio, an important skill for financial market analysts in banks, hedge funds, insurance companies, and other financial services and investment firms. Using the R programming language with Microsoft Open R and RStudio, you will use the two main tools for calculating the market risk of stock portfolios: Value-at-Risk (VaR) and Expected Shortfall (ES). You will need a beginner-level understanding of R programming to complete the assignments of this course.

This module goes over the use of R and RStudio, retrieving data from different data sources (FRED at the Federal Reserve Bank of St. Louis and Yahoo!Finance), and the calculation of returns.

What's included

5 videos3 readings7 assignments

5 videosTotal 29 minutes

Introduction9 minutes
Retrieving Data from FRED7 minutes
Calculating Daily Returns6 minutes
Calculating Longer Returns3 minutes
A Simple Example3 minutes

3 readingsTotal 27 minutes

Exercise 1 - Introduction to R and R Studio20 minutes
Report a problem with the course5 minutes
Quiz Instructions2 minutes

7 assignmentsTotal 165 minutes

Quiz 1.1 30 minutes
Quiz 1.2 30 minutes
Quiz 1.3 30 minutes
Quiz 1.4 30 minutes
Exercise 2 - Retrieving data from Yahoo!Finance 15 minutes
Exercise 3 - Calculating Daily Returns15 minutes
Exercise 4 - Longer Horizon Returns15 minutes

This module covers how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns are normally distributed.

What's included

4 videos1 reading8 assignments

4 videosTotal 32 minutes

Distribution of Returns7 minutes
Value-at-Risk (VaR)8 minutes
Expected Shortfall (ES)6 minutes
Using Simulation to Estimate VaR and ES11 minutes

1 readingTotal 2 minutes

Quiz Instructions2 minutes

8 assignmentsTotal 180 minutes

Quiz 2.1 30 minutes
Quiz 2.2 30 minutes
Quiz 2.3 30 minutes
Quiz 2.4 30 minutes
Exercise 5 - Estimating Parameters of the Normal Distribution15 minutes
Exercise 6 - Estimating VaR of the Normal Distribution15 minutes
Exercise 7 - Estimating ES of the Normal Distribution15 minutes
Exercise 8 - Estimating VaR and ES via Simulation15 minutes

This module covers how to test for normality of returns, and how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns are not normally distributed.

What's included

4 videos1 reading7 assignments

4 videosTotal 57 minutes

Non-normal Distributions15 minutes
Student-t Distribution14 minutes
Rescaled t Distribution Model15 minutes
VaR and ES for Multi-day Horizon13 minutes

1 readingTotal 2 minutes

Quiz Instructions2 minutes

7 assignmentsTotal 165 minutes

Quiz 3.1 30 minutes
Quiz 3.2 30 minutes
Quiz 3.3 30 minutes
Quiz 3.4 30 minutes
Exercise 9 - Skewness, Kurtosis, Jarque-Bera Test for Normality15 minutes
Exercise 10 - Estimate Parameters of the Scaled Student's-t Distribution15 minutes
Exercise 11 - Estimate VaR and ES at 10-day Horizon15 minutes

This module covers how to test for the presence of volatility clustering, and how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns exhibit volatility clustering.

What's included

9 videos2 readings6 assignments

9 videosTotal 74 minutes

Future vs Historical Distribution13 minutes
Volatility Clustering7 minutes
GARCH11 minutes
Estimation: rugarch Package10 minutes
GARCH(1,1) - t4 minutes
Diagnostic Tests8 minutes
Using the ugarchboot Function10 minutes
Using the ugarchroll Function5 minutes
Course Summary4 minutes

2 readingsTotal 12 minutes

Quiz Instructions2 minutes
Share your learning experience10 minutes

6 assignmentsTotal 150 minutes

Quiz 4.1 30 minutes
Quiz 4.2 30 minutes
Quiz 4.3 30 minutes
Quiz 4.4 30 minutes
Exercise 12 - Serial Correlation, Volatility Clustering, GARCH15 minutes
Exercise 13 - VaR and ES for GARCH bootstrap15 minutes

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Instructor

Instructor ratings

(103 ratings)

David Hsieh

Duke University

1 Course19,645 learners

Offered by

Duke University

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Reviewed on Jul 10, 2020

The basic of financial risk management are provided with very clear theoretical background and exercises to learn it practically!

Reviewed on Apr 5, 2021

good course, I would have gone deeper in the last part, about GARCH modelling

Reviewed on Jul 6, 2020

This course has been very well planned and structured. I enjoyed taking it. Thank you.

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