Financial Data Analytics with R: Methods and Applications
Financial Data Analytics with R: Methods and Applications
Understanding and applying financial analysis
This further education programme provides a very application-oriented insight into the "R" software with a focus on the financial services industry. For participants who have no prior knowledge of R, an optional introduction is offered at the beginning.
The course will then focus on multivariate methods, machine learning techniques, time series and predictive modelling.
In addition, various R packages and applications for different IT infrastructures will be presented and applied with a special focus on financial service providers.
Depending on the focus of the audience, in-depth topics from the following pool will also be covered: Parametric volatility modelling in R, interest rate models / fixed income, predictive models in pricing, uncertainty measurement and exposure calculation in loss reserving, longevity risk and mortality tables, calculation of value at risk and expected shortfall in R, copulas in R and credit risk in R.
In this module you will gain practical experience in dealing with statistical data analyses in the insurance and finance sector.
This further education programme is aimed at self-employed persons and
employees in the financial sector who would like to receive targeted training in risk management
.
