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How to build an algorithmic trading system with Python (based on 3 years of fixing mistakes and gaining confidence + results) A thread:
Today I want to share a little bit about what I've learned along my journey in algorithmic trading. It took me 3 years to grow my confidence. I made a ton of mistakes. But now my portfolio is $6,500,000. I'm still learning. But here's what worked for me:
1) Data Sourcing & Quality • Start with reliable financial data. • Scrub for inconsistencies & fill missing values. • Free data sources exist, but for serious work, consider paid APIs (e.g., from broker APIs or market data providers).
I use these 2 data sources (paid): • Nasdaq DataLink (Bulk price data) • Financial Modeling Prep (fundamental data) To get started I recommend these free resources: • yfinance • openbb
2) Alpha Model • Core logic: generates buy/sell signals. • Could be mean reversion, trend following, or ML-based. In Python, I perform quant research with: pandas, NumPy, scikit-learn I use these to test different hypotheses quickly.
3) Portfolio Construction • Allocate positions based on signal confidence & risk tolerance. • Use Python frameworks (e.g., Riskfolio for optimization). • Equal-weight, risk-parity, or custom weighting—depends on your strategy & risk profile.
4) Transaction Costs & Execution • Account for commissions, slippage, and order types in your backtests. • Model these costs realistically (even if estimates). • Python tip: incorporate slippage/commissions logic directly into your trade simulations I use Zipline & VectorBT
5) Risk Management • Ongoing monitoring of drawdowns & exposure. • Set stop losses, trailing stops, or volatility-based position sizing. • Tools like pandas & plotly help visualize risk metrics & performance over time.
7) Putting It All Together • The pipeline: Data → Alpha → Portfolio Construction → Execution → Risk Management. • Write modular code to keep each component testable & maintainable. • Start simple; refine iteratively as you gain insights.
Want to learn how to get started with algorithmic trading with Python? Then join us on February 12th for a live webinar, how to Build Algorithmic Trading Strategies (that actually get results) Register here (500+ registered): <a target="_blank" href="https://learn.quantscience.io/qs-register" color="blue">learn.quantscience.io/qs-register</a>
