Quantitative Risk Management in R Data Camp

Overview

Context

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. 

What you will learn during this Quantitative Risk Management in R course offered by Data Camp:

• 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.
• You will learn about graphical and numerical tests of normality, apply them to different datasets, and consider the alternative Student t model.
• 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.
• You will briefly learn about the concept of value-at-risk and simple methods of estimating VaR based on historical simulation.