Mastering Backtesting for Algorithmic Trading

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Hudson and Thames Quantitative Research

8:31:50

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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.mp4

01:44

2. Lecture Backtesting Tutorial.mp4

35:58

3. Notebook Practical Downloading Price Data with YFinance.html

4.1 QuantStats.html

4. Backtest Statistics and Libraries in Python.mp4

26:14

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.mp4

45:09

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).mp4

27:45

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.mp4

13:23

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.mp4

05:04

3. A Taxonomy of Quant Models.mp4

06:36

4. How to Develop a Quant Strategy.mp4

07:59

5. 9 Tips for Better Model Development.mp4

07:45

6. External Lecture Enhancing Statistical Significance of Backtests.html

5. The Importance of Causality in your Experiment Design

1. Introduction to Causality in Finance.mp4

33:53

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.mp4

44:08

6. What Not to Do!

1. Lecture Introduction.mp4

05:35

2. Paper Seven Sins of Quantitative Investing.html

3. Lecture The 7 Sins of Quantitative Investing.mp4

11:29

4. Paper The Four Horsemen of Machine Learning in Finance.html

5. Lecture The Four Horsemen of Machine Learning in Finance.mp4

13:20

6. Principles for Effective Machine Learning in Finance.mp4

10:42

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.mp4

41:16

3. Paper Detection of False Investment Strategies.html

4. Lecture Detection of False Investment Strategies.mp4

22:44

5. Paper Backtesting (An Alternative Approach to the DSR and PSR).html

6. Lecture on the paper Backtesting.mp4

37:52

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.mp4

39:53

4. Paper When do stop-loss rules stop losses.html

5. Lecture When do Stop-Loss Rules Stop Losses.mp4

43:21

6. Paper A Practitioner Perspective on Trading and Implementation of Strategies.html

7. Lecture A Practitioner Perspective on Trading and Implementation of Strategies.mp4

30:00

Description

Unlock the Power of Historical Simulations – Hands on Approach

What You'll Learn?

Master the Art of Backtesting: gain the skills to design and run your own custom backtests using historical data, starting from the very basics to advanced.
Spot and Avoid False Strategies: Uncover the secrets to identifying deceptive investment strategies.
Learn from Leading Experts: Benefit from the wisdom of pioneers in the field. Our curriculum is built around groundbreaking research and publications.
Infuse Causality in Your Strategies: Elevate your trading approach by integrating causal reasoning.
Adopt Best Practices in Quantitative Research: Forge your path in quantitative equity strategies using industry best practices.
Practical Insights and Real-World Application: This course doesn't just stop at theory. You'll get hands-on experience building your own backtester in Python
Innovate with Confidence: Equip yourself with the knowledge to not just follow but innovate in the field of quantitative finance.

Who is this for?

Aspiring quant traders and analysts looking to understand backtesting.

Finance professionals who want to incorporate data-driven methods into their trading strategies.

Students and academics interested in quantitative finance.

Hobbyists looking to learn more about algorithmic trading.

What You Need to Know?

Familiarity with Python programming

Basic understanding of financial markets and trading.

Linear algebra and statistics is helpful

Ability to read mathematical equations

More details

Description
This course is designed to equip you with the tools and knowledge needed to effectively backtest trading strategies using Python. It is tailored for those who want to test and validate their trading ideas with historical market data, ensuring a robust and data-driven approach to trading.

Building Your Own Backtester in Python: Dive into the technicalities of building a backtester from scratch. Learn to code in Python and use popular libraries to create a versatile and reusable backtesting framework.
Before You Backtest - Use This Protocol!: Understand the essential steps to prepare for backtesting. This module focuses on data collection, hypothesis formation, and setting up testing parameters.
Best Practices in Research for Quantitative Equity Strategies: Learn the industry-standard research methodologies that quantitative analysts use for developing equity strategies. We cover data analysis techniques, statistical tests, and more.
The Importance of Causality in Your Experiment Design: Understand the role of causality in trading strategy design. Learn how to differentiate between correlation and causation to build more effective trading strategies.
What Not to Do!: A critical look at common pitfalls in strategy backtesting. Learn to identify and avoid mistakes that can lead to inaccurate conclusions and poor strategy performance.
Detecting False Investment Strategies: Equip yourself with the knowledge to spot and avoid strategies that appear profitable but are actually flawed due to overfitting, data-snooping biases, or other errors.
Bonus Lectures: Engage with additional content that delves into advanced topics, real-world case studies, and emerging trends in quantitative finance.
Who this course is for:
Aspiring quant traders and analysts looking to understand backtesting.
Finance professionals who want to incorporate data-driven methods into their trading strategies.
Students and academics interested in quantitative finance.
Hobbyists looking to learn more about algorithmic trading.

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Hudson and Thames Quantitative Research is a company known for its contributions to the field of quantitative finance, particularly in the development and application of advanced mathematical and statistical methods to financial data. Their work typically involves the creation of algorithms and models to facilitate investment decisions, risk management, and trading strategies.

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language english
Training sessions 22
duration 8:31:50
Release Date 2024/04/13

Mastering Backtesting for Algorithmic Trading

1. Useful Resources

2. Build Your Own Backtester in Python

3. Before you Backtest - Use this Protocol!

4. Best Practices in Research for Quantitative Equity Strategies

5. The Importance of Causality in your Experiment Design

6. What Not to Do!

7. Detecting False Investment Strategies

8. Extra Content Position Sizing, Stop Losses, and Costs

Description

What You'll Learn?

Who is this for?

What You Need to Know?

More details

Who this course is for:

User Reviews

Rating

Forex

Financial Trading

Day Trading

Algorithmic Trading

Stock Trading

Options Trading

Hudson and Thames Quantitative Research

Udemy

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