DataCamp
FreeQuantitative Risk Management in R
4.9(83)15k studentsBEGINNEREnglish
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Course Overview
The Quantitative Risk Management in R course introduces essential quantitative techniques for evaluating financial portfolio risk. You will learn to collect risk-factor return series and investigate empirical properties like volatility and non-normality to construct reliable risk models.
Who Is This Course For?
This introductory course is aimed at analysts and professionals in banking, insurance, and asset management looking to build foundational risk modeling skills in R.
Key Takeaways
- Work with financial risk-factor return series in R.
- Examine stylized facts of financial data, including non-normality and volatility.
- Calculate portfolio Value-at-Risk (VaR) estimates.
- Understand underlying drivers of portfolio risk behavior.
About this course
In Quantitative Risk Management (QRM), you will build models to understand the risks of financial portfolios. This is a vital task across the banking, insurance and asset management industries. The first step in the model building process is to collect data on the underlying risk factors that affect portfolio value and analyze their behavior. In this course, you will learn how to work with risk-factor return series, study the empirical properties or so-called "stylized facts" of these data - including their typical non-normality and volatility, and make estimates of value-at-risk for a portfolio.
Price
Free
This course is free to enrol.
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