- Uses Prof. Daniel P. Palomar and the Convex Research group's quantitative tools to model stocks, construct and backtest risk parity/budgeting portfolios.
- Selects list of tickers to model and construct a portfolio using factor based models (TBD)
- Fits Multivariate Student's t distribution to a list of stocks using fitHeavyTail
- Constructs a risk parity/budgeting portfolio using riskParity.py
- Constructs sparse portfolio using sparseIndexTracking
- Backtests returns of constructed portfolios
- Python
- rpy2
- R compiler
- requirements.txt
| Portfolio | FRXE.L (%) | UC90.L (%) | VUSA.L (%) |
|---|---|---|---|
| Risk Parity | 56.6 | 24.5 | 18.9 |
| Risk Budget (60%, 20%, 20%) | 47.4 | 20.0 | 32.6 |
| Equal Weight | 33 | 33 | 33 |
| Ticker | Weight (%) |
|---|---|
| VMID.L | 30.6 |
| VUKE.L | 24.1 |
| V3AM.L | 45.3 |