Backtesting Algorithmic Trading Strategies with Python by Matt Dancho

Backtesting Algorithmic Trading Strategies with Python by Matt Dancho – Instant Download!

Overview

Trading isn’t just about picking stocks—it’s about building resilient portfolios backed by data. The Backtesting Algorithmic Trading Strategies with Python by Matt Dancho course gives you the tools to do exactly that.

This 912 MB training program priced at $23.1 walks you step by step through designing, building, and backtesting profitable algorithmic trading portfolios using Python — even if you’ve never written a line of code before. It focuses on portfolio-based trading, risk management, and strategy validation, helping you trade smarter and grow your investments responsibly.

Led by Matt Dancho, founder of Business Science and an expert in financial data science, the course combines 250+ hours of research into one structured, beginner-friendly program. By the end, you’ll have your own working Python Quant Lab, four tested portfolio strategies, and the confidence to make data-driven investment decisions.

Backtesting Algorithmic Trading Strategies with Python – Free Download Video Sample:

Why it matters

Most beginner traders fail because they:

• Don’t know where to start with algorithmic trading.

• Rely on risky single-stock strategies.

• Lack experience with financial data and backtesting.

The result? They lose money, time, and confidence.

The Backtesting Algorithmic Trading Strategies with Python course matters because it gives you a proven 3-step framework for building sustainable, professional-grade trading portfolios — the same process used by institutional investors.

With the right setup, you’ll learn how to:

• Build a diversified portfolio that minimizes risk.

• Backtest your strategies across market conditions.

• Implement risk-adjusted trading techniques.

• Grow your investments systematically, not emotionally.

This course removes the complexity so you can focus on what really matters — results.

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Benefits

1. Build Your Own Quant Lab

Get everything you need to set up your Python trading environment and start testing strategies — no prior coding experience required.

2. Proven 3-Step Process

Follow a professional, portfolio-based system to create responsible, risk-managed trading plans.

3. Backtest Like a Pro

Use Zipline Reloaded to test performance under various conditions — including rebalancing, slippage, and commissions — for realistic results.

4. Gain Access to Multiple Strategies

Implement four portfolio trading strategies including volatility targeting and risk optimization to boost returns and stability.

5. Free and Premium Market Data Solutions

Access both free and premium professional data to power your backtests — with ready-to-use Python scripts provided.

6. Code-Driven, Real-World Learning

No fluff — you’ll get hands-on Python templates, code examples, and data workflows you can apply immediately to your trading.

7. Expand Your Knowledge with Bonuses

Access advanced material covering 21,000+ U.S. equities and portfolio strategies built for different market conditions.

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What you’ll learn

The course breaks down algorithmic portfolio trading into three clear, actionable steps — each designed to make you proficient in backtesting and data analysis.

Step 1 – Trading Project & Python Quant Lab Setup

• Install the Quant Stack Python Software.

• Create your algorithmic trading environment.

• Organize your project for efficiency and scalability.

• Build the foundation for backtesting and portfolio construction.

Step 2 – Creating a Profitable Algorithmic Portfolio Strategy

• Learn volatility targeting with auto-rebalancing to control risk dynamically.

• Use Riskfolio-Lib to build optimized, diversified portfolios.

• Apply the Ray Dalio Bridgewater Cheat Code for long-term stability.

• Understand how to use Python to automate calculations and improve consistency.

Step 3 – Professional Backtesting Techniques

• Learn event-based backtesting using Zipline Reloaded.

• Include slippage, fees, and rebalancing for realistic performance metrics.

• Avoid common pitfalls and overfitting errors.

• Measure returns, volatility, and drawdowns across timeframes.

Each step is explained with real examples, interactive code templates, and guidance for all experience levels.

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Key features / modules

• Comprehensive Python backtesting tutorials.

• 4 portfolio trading strategies focused on risk management.

• Quant Lab setup guide with environment configuration.

• 250+ hours of research condensed into clear steps.

• Bonus data modules for both free and premium datasets.

• Code templates for automated trading and portfolio optimization.

• Lifetime access to course updates and materials.

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Bonuses

Bonus 1 – Professional Data for 21,000+ US Equities

Get Python templates to ingest professional-grade market data and convert it into Zipline bundles for high-quality backtesting.

Bonus 2 – Free Market Data Setup

Learn how to pull and prepare free market data for backtesting if you’re just getting started.

Bonus 3 – Top 3 Variations of Volatility Targeting Strategy

Access advanced strategies tailored for different market conditions, including:

• Hierarchical Risk Parity (HRP)

• CVaR Risk Measure

• Risk Factor using Principal Component Regression (PCR)

These bonuses ensure you can test and adapt strategies in any environment — from bullish trends to volatile downturns.

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Who it’s for

The Backtesting Algorithmic Trading Strategies with Python by Matt Dancho course is perfect for:

• Beginner traders who want to build confidence and avoid emotional decision-making.

• Data analysts and programmers seeking to apply Python to quantitative finance.

• Portfolio managers who want to validate strategies before trading live.

• Financial professionals looking to integrate algorithmic trading into their workflow.

• Anyone ready to grow investments responsibly with data-backed systems.

If you want to bridge the gap between trading ideas and real performance, this course gives you the framework and confidence to do it right.

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Conclusion

Backtesting Algorithmic Trading Strategies with Python by Matt Dancho is your complete roadmap to mastering portfolio trading with data science.

Instead of risking money on untested strategies, you’ll learn to analyze, validate, and optimize trading systems using Python — the same tools used by hedge funds and professional quants. With hands-on coding, ready-to-use templates, and professional guidance, you’ll gain the skills to manage risk, grow wealth, and make smarter investment decisions.

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Ready to backtest like a pro?

For just $23.1, gain access to 912 MB of professional training, templates, and code that make algorithmic trading accessible and profitable.

👉 Enroll today in Backtesting Algorithmic Trading Strategies with Python by Matt Dancho and start building reliable, data-driven portfolios that grow responsibly.