Python, NumPy, pandas, yfinance, Matplotlib, SciPy

A pipeline built in python that inputs a list of tickers, and filters them based on trading volumes, currencies, and valid listing.
Uses statistics like Alpha, Beta, and Sharpe Ratios to pick optimal stocks
Builds an optimal portfolio, starting with $1 million CAD initial investment, based on optimal returns over the S&P 500 index
Achieved a +1.70% return over the S&P 500 index in December 2025 Alone