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Financial Risk Management with R

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Financial Risk Management with R

Name: Financial Risk Management with R
Rating: 4.319066147859922 (257 reviews)

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

Instructor: David Hsieh

19,549 already enrolled

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

257 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.

257 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

91% of learners achieved a positive career outcome

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Build your subject-matter expertise

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.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

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.

Module details

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

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

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
Quiz 2.1 30 minutes
Quiz 2.2 30 minutes
Quiz 2.3 30 minutes
Quiz 2.4 30 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

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
Quiz 3.1 30 minutes
Quiz 3.2 30 minutes
Quiz 3.3 30 minutes
Quiz 3.4 30 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.