Course
Quantitative Risk Management in R
BasicSkill Level
Updated 01/2026RApplied Finance5 hr18 videos55 Exercises4,350 XP15,854Statement of Accomplishment
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Prerequisites
Manipulating Time Series Data in R1
Exploring Market Risk-Factor Data
In this chapter, you will learn how to form return series, aggregate them over longer periods and plot them in different ways. You will look at examples using the qrmdata package.
2
Real World Returns are Riskier Than Normal
In this chapter, you will learn about graphical and numerical tests of normality, apply them to different datasets, and consider the alternative Student t model.
3
Real World Returns are Volatile and Correlated
In this chapter, you will learn about volatility and how to detect it using act plots. You will learn how to apply Ljung-Box tests for serial correlation and estimate cross correlations.
4
Estimating Portfolio Value-at-Risk (VaR)
In this chapter, the concept of value-at-risk and simple methods of estimating VaR based on historical simulation are introduced.
Quantitative Risk Management in R
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FAQs
What financial risk measures does this course teach me to calculate?
You will learn to estimate value-at-risk (VaR) for a portfolio using historical simulation, which is a core risk measure in banking, insurance, and asset management.
What are the stylized facts of financial returns covered in this course?
You will study non-normality, heavy tails, volatility clustering, and serial correlation in real financial return series, comparing them against the normal and Student t distributions.
Which R packages are used in the course?
You will use the qrmdata package for financial return datasets and apply graphical normality tests, Ljung-Box tests for serial correlation, and volatility analysis tools available in R.
Do I need a finance background to take this course?
A finance background is helpful but not required. You do need Intermediate R and experience with time series data manipulation in R to handle the coursework.
What industries use the quantitative risk management skills taught here?
Banking, insurance, and asset management all require professionals who can model portfolio risk, assess return distributions, and estimate value-at-risk.
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