⚡ Optimize Bitcoin price simulation with NumPy vectorization

[EiJackGH]

💡 What: Vectorized the simulate_bitcoin_prices function in bitcoin_trading_simulation.py using NumPy. Replaced the iterative loop with np.random.normal and np.cumprod. Added unit tests in test_bitcoin_trading.py and updated .gitignore.

🎯 Why: The original implementation used a Python loop which is slow for large number of days. Vectorization significantly improves performance.

📊 Measured Improvement:

• Baseline: ~9.04 seconds for 1000 iterations of 2000 days.
• Optimized: ~0.13 seconds for 1000 iterations of 2000 days.
• Speedup: ~69x faster.

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PR created automatically by Jules for task 11112607882759080789 started by @EiJackGH

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