The client, a leading asset management company, wanted to identity parameters that can help in analyzing and assessing the security selection skill of a portfolio manager in a portfolio
Execution highlights
Employed multi-factor performance attribution model to study active returns breakdown to identify skill-based returns.
Aggregate time-series data for all funds to create panel data and in turn perform analysis to assess manager’s skill and also highlight its persistence over a long timeframe
Performed regression analysis along with various other descriptive analysis using MATLAB. Used independent variables like risk, duration, volatility and the dependent variable was active returns.
Wrote efficient codes for running regressions & performing various robustness tests. Automated entire process starting from loading new data feeds on a monthly basis to running the regression model
Results were significant with factor exposures explaining excess returns for portfolio to a great extent
How Crisil GR&RS made a difference
Client published the findings from the study as part of research paper, and attributed Crisil GR&RS associate for the excellent work
This study helped in analyzing new strategies to generate active returns