وب سایت تخصصی شرکت فرین
دسته بندی دوره ها

Mastering Backtesting for Algorithmic Trading

سرفصل های دوره

Unlock the Power of Historical Simulations – Hands on Approach


1. Useful Resources
  • 1. Free 1 Month MlFinLab License.html
  • 2. Join the Reading Group.html

  • 2. Build Your Own Backtester in Python
  • 1. Lecture Introduction to Backtesting
  • 2. Lecture Backtesting Tutorial
  • 3. Notebook Practical Downloading Price Data with YFinance.html
  • 4.1 QuantStats.html
  • 4. Backtest Statistics and Libraries in Python
  • 5. External Lecture Using Pyfolio to Analyze your Trading Strategies.html
  • 6. External Lecture QuantStats - Portfolio Analytics with Python Tutorial.html
  • 7. Notebook Practical Build your Own Backtest.html
  • 8. Paper The Impact of Volatility Targeting.html
  • 9. Lecture The Impact of Volatility Targeting
  • 10. What About Transaction Costs.html
  • 11. External Lecture When Should You Build Your Own Backtester.html
  • 12.1 Backtrader.html
  • 12.2 Lean Event Driven Backtester (QuantConnect).html
  • 12.3 VectorBT.html
  • 12.4 Zipline Event Driven Backtester (Quantopian).html
  • 12. Overview of Backtesting Platforms (Python)
  • 13. Recommended Readings for Building your Own Backtester.html

  • 3. Before you Backtest - Use this Protocol!
  • 1. Paper A Backtesting Protocol in the Era of Machine Learning.html
  • 2. The Protocol.html
  • 3. Lecture 7 Point Backtesting Protocol

  • 4. Best Practices in Research for Quantitative Equity Strategies
  • 1. Paper Best Practices in Research for Quantitative Equity Strategies.html
  • 2. Heart of the Quantitative Model Data
  • 3. A Taxonomy of Quant Models
  • 4. How to Develop a Quant Strategy
  • 5. 9 Tips for Better Model Development
  • 6. External Lecture Enhancing Statistical Significance of Backtests.html

  • 5. The Importance of Causality in your Experiment Design
  • 1. Introduction to Causality in Finance
  • 2.1 Causal Factor Investing Can Factor Investing Become Scientific.html
  • 2. Paper Causal Factor Investing Can Factor Investing Become Scientific.html
  • 3.1 ADIA Labs Call for Papers.html
  • 3. Lecture Scientific Discovery in Quantitative Finance

  • 6. What Not to Do!
  • 1. Lecture Introduction
  • 2. Paper Seven Sins of Quantitative Investing.html
  • 3. Lecture The 7 Sins of Quantitative Investing
  • 4. Paper The Four Horsemen of Machine Learning in Finance.html
  • 5. Lecture The Four Horsemen of Machine Learning in Finance
  • 6. Principles for Effective Machine Learning in Finance
  • 7. External Lecture 10 Ways Backtests Lie.html
  • 8. Paper The 10 Reasons Most Machine Learning Funds Fail.html
  • 9. External Lecture The 7 Reasons Most Machine Learning Funds Fail.html

  • 7. Detecting False Investment Strategies
  • 1. Paper The False Strategy Theorem.html
  • 2. Lecture The False Strategy Theorem
  • 3. Paper Detection of False Investment Strategies.html
  • 4. Lecture Detection of False Investment Strategies
  • 5. Paper Backtesting (An Alternative Approach to the DSR and PSR).html
  • 6. Lecture on the paper Backtesting
  • 7. Paper Evaluating Trading Strategies.html
  • 8.1 The Risks of Historical Backtests.html
  • 8. External Lecture The Risks of Historical Backtests.html

  • 8. Extra Content Position Sizing, Stop Losses, and Costs
  • 1. Paper Risk-Constrained Kelly Gambling.html
  • 2. Paper The Kelly Criterion in Blackjack Sports Betting, and the Stock Market.html
  • 3. Lecture Four Approaches to Kelly Bet Sizing
  • 4. Paper When do stop-loss rules stop losses.html
  • 5. Lecture When do Stop-Loss Rules Stop Losses
  • 6. Paper A Practitioner Perspective on Trading and Implementation of Strategies.html
  • 7. Lecture A Practitioner Perspective on Trading and Implementation of Strategies
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