Add Robust Betas to Performance Analytics

Robust statistics are useful in finance since all classical estimates are vulnerable to extreme distortion by outliers. Because financial data has outliers to various degrees, practitioners need robust estimates that:

• Are not strongly influenced by outliers,
• Fit a good model to the bulk of the data,
• Detect and ignore outliers, and
• Provide for stable inference and prediction

PerformanceAnalytics is a collection of econometric functions for performance and risk analysis, long considered a core package by the finance community. In addition to standard risk and performance metrics, this package aims to assist practitioners and researchers in using the latest research in the analysis of non-normal return streams.

So I will be doing the following 2 things:-

• Creating functionality for calculating outlier-insensitive risk estimates in the Capital Asset Pricing Model
• Publishing a vignette on CRAN to demonstrate new features & formulating unit-tests to ensure consistency

Impact:-

• Facilitating faster development & easier maintenance by reducing the technical debts of the package
• Aiding 120K+ risk professionals & researchers in making better risk analysis informed investment choices