raghuramshankar / quant-portfolios

Construct portfolios informed by quantitative analysis

Quant Portfolios

• Uses Prof. Daniel P. Palomar and the Convex Research group's quantitative tools to model stocks, construct and backtest risk parity/budgeting portfolios.

Tasks/Tools:

• 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

Requirements:

• Python
• rpy2
• R compiler
• requirements.txt

Risk Parity Portfolio:

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

Sparse Portfolio:

Ticker	Weight (%)
VMID.L	30.6
VUKE.L	24.1
V3AM.L	45.3