Monte Carlo Simulation of a Canadian Stock Portfolio

🧠 What does uncertainty look like? Maybe… something like this.

When we think about investing in stocks, ETFs, businesses—whatever it is—there’s always that little voice in our heads:

• “What if it drops tomorrow?”
• “What if I had bought in earlier?”
• “What if I hadn’t sold?”
• “What if… I had known?”

So, I decided to stop ignoring it.

Using a small Python algorithm, I explored 200 plausible futures of a Canadian stock portfolio 🇨🇦 (RBC, Shopify, TD, Barrick Gold—good old TSX).

📊 Each scenario follows its own path, shaped by:

• historical data,
• expected returns,
• volatility, and
• correlations between stocks.

🎢 The result: a ballet of curves

• Some paths skyrocket 📈
• Others plummet 📉
• None of them are the truth… but all of them are possible

👨‍💻 Tools used:

• Python
• pandas, numpy, matplotlib
• yfinance for stock market data

📷 Visualization:

🏷️ Tags:

#Investing, #Simulation, #MonteCarlo, #Finance, #Python, #Risk, #DataViz, #Canada, #TSX

💬 If you’ve ever wondered what uncertainty might look like… well, it might look something like this.