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.



Financial Risk Management with R
This course is part of Entrepreneurial Finance: Strategy and Innovation Specialization

Instructor: David Hsieh
Access provided by Albertsons
18,944 already enrolled
(253 reviews)
Skills you'll gain
- Portfolio Management
- Securities (Finance)
- Financial Data
- Financial Trading
- Time Series Analysis and Forecasting
- Statistical Programming
- Probability Distribution
- Statistical Modeling
- Financial Modeling
- Financial Market
- Market Data
- Risk Modeling
- Risk Management
- Securities Trading
- R (Software)
- R Programming
- Risk Analysis
- Estimation
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There are 4 modules in 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
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
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
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
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Reviewed on Jan 22, 2023
The material was concise and reinforced what I had learned.
Reviewed on Mar 20, 2021
Challenging, but worthwhile -- would recommend approaching over weeks, and not rushing through.Do not need a strong background in Statistics, but would definitely help understand the terminology.
Reviewed on Jul 6, 2020
This course has been very well planned and structured. I enjoyed taking it. Thank you.
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