Mean Reversion Strategies In Python
(Торговые стратегии на основе возвращения к среднему (на языке Python)
by Dr. Ernest P. Chan
Learn the concepts, coding, and implementation of four mean reversion strategies in Python by Ernest Chan
This course covers basic concepts, exercises and practical implementation of four mean reversion trading strategies. It has a mix of videos, eBooks, MCQs, iPython notebook documents and Interactive coding exercises to enhance your learning experience.
Краткое содержание (полное - см.под спойлером ниже)
1. Стационарность временных рядов
2. Коинтеграция
3. Триплеты (синтетические фин.инструменты, линейн.комбинация трёх инструментов)
4. Период полужизни
5. Риск-менеджмент
6. Лучшие рынки для парного трейдинга
7. Индексный арбитраж
8. Портфель
9. Выводы и исходные тексты программ
Видеокурс на англ. языке + субтитры (оригинальные авторские, а не машинный перевод)
This is a certification course by Quantinsti - Asia’s pioneer Algorithmic Trading Research and Training Institute focused on preparing financial market professionals for the contemporary field of Algorithmic and High-Frequency Trading.
This is the first time we are launching the course in collaboration with Ernest Chan who is the managing director of QTS Capital Management, on Quantra. This course will discuss four types of mean reverting trading strategies.
First, we will discuss stationarity for a single price series, and create a mean-reverting trading strategy if the price series is stationary.
Second, we will learn about a portfolio of instruments that are cointegrated and create a mean-reverting strategy on pairs and triplets.
The third strategy which we will discuss in this course is for a basket of stocks, that is Index Arbitrage strategy, which is also an extension of pairs and triplets.
The final strategy that we will learn is Long-Short Portfolio, which is based on cross-sectional mean reversion.
Along with these strategies, we will also discuss different statistical techniques namely Augmented Dickey-Fuller (ADF) test, CADF test, Half-life, Johansen test, etc. for detecting stationarity and cointegration of a portfolio of instruments.
Apart from the theoretical concepts, a downloadable Python code is provided for all the four strategies along with lots of hands-on-coding in interactive coding exercises.
Course Modules
Section 1: Stationarity of Time Series
Prologue 3min 39sec
Introduction to stationarity 2min 18sec
Quiz: Stationarity 2min
Quiz: Mean reversion trading 2min
Quiz: Temporary mean reversion 2min
Quiz: Statistical test 2min
ADF test 3min 45sec
Math behind ADF Test (optional) 5min 0sec
IE: Import library and read CSV 5min
IE: Test statistics 5min
Mean reversion strategy 1min 58sec
Mean Reversion Strategy Code 10min 0sec
IE: Moving average and std dev 5min
IE: Upper and lower band 5min
IE: Long entry and exit 5min
IE: Short entry and exit 3min
IE: Long and short positions 5min
IE: Forward fill missing positions 5min
IE: Consolidate the positions 5min
IE: Compute pnl 5min
Recap 1min 47sec
Section 2: Cointegration
Quiz: Cointegration 2min
Introduction to cointegration 3min 12sec
Quiz: Correlation 2min
Hedge Ratio 5min 48sec
Quiz: Hedge Ratio 2min
Hedge Ratio Code 2min 26sec
IE: Import library nullhrs 5min
IE: Hedge Ratio 5min
CADF Test 3min 44sec
IE: CADF Test 5min
Order dependence of CADF Test 5min 0sec
Mean Reversion Strategy 2min 55sec
Mean Reversion Strategy Code 10min 0sec
IE: Long Entry and Exit 5min
IE: Pnl Pairs 5min
Recap 2min 16sec
Section 3: Triplets
Breakdown of GLD-GDX 5min 5sec
Quiz: Breakdown of cointegration 2min
Quiz: Significance of cointegration 2min
Surviving breakdown of cointegration 5min 17sec
Quiz: Surviving breakdown 2min
Quiz: Breakdown remedies 2min
Quiz: Optimization problems 2min
Eigenvalues and Eigenvectors 2min 0sec
Johansen Test 6min 27sec
Quiz: CADF shortcomings 2min
Quiz: Linear combination 2min
IE: GLD-GDX cointegration test 4min
Mean reversion of triplets 4min 12sec
IE: GLD-GDX-USO cointegration test 4min
Quiz: Cointegration Test 2min
Quiz: Taking positions 2min
Recap 1min 11sec
Section 4: Half Life
Practical Importance of Half Life 4min 12sec
Quiz: Half life 2min
Quiz: Half life formula 2min
IE: Computing half-life of GLD-GDX 5min
Section 5: Risk Management
Stop-loss 5min 0sec
Section 6: Best Markets To Pair Trade
Best Markets To Pair Trade 5min 19sec
Quiz: ETFs 2min
Quiz: Stocks 2min
Quiz: Currencies and Futures 2min
CL vs BZ 10min 0sec
Crack Spread 10min 0sec
Section 7: Index Arbitrage
Index Arbitrage 3min 49sec
Quiz: Index Arbitrage 2min
Quiz: Custom Basket 2min
Index Arbitrage Strategy Code 10min 0sec
Difficulties in Index Arbitrage 2min 0sec
Section 8: Long Short Portfolio
Long-Short portfolio Strategy 3min 44sec
Quiz: Long-Short Portfolio 2min
Quiz: Strategy Formula 2min
Long-Short Portfolio Strategy Code 10min 0sec
IE: Stock Returns 5min
IE: Market Returns 5min
IE: Dollar Allocation 5min
IE: Sharpe Ratio 5min
Analysis of Strategy Performance 5min 0sec
Section 9: Summary
Summary 3min 52sec
Downloadable Resources
Who can benefit from this course
The overall aim of this course is to provide a practical guide to mean reverting trading strategies that can be readily implemented by both retail and institutional traders. This course can be used by traders, analysts, researchers, teaching professionals, and students. Anyone who wants to learn about mean reverting strategies and wants to optimize their strategy performance is perfectly suited for this course.
Pre requisites
A basic knowledge of financial market and mathematics will boost your understanding of different concepts and strategies taught in this course. Also, all the strategies are implemented in Python so a basic understanding of python will be beneficial. We recommend students with no Python background, to undertake our course “Python for Trading” before enrolling for this course.
Benefits from enrolling the course
- Learn about stationarity and test for stationarity of a single price series.
- Learn about cointegration and test for cointegration of two price series.
- Learn to create mean reverting strategies and understand practical problems encountered in live trading.
- Learn about how to create an index arbitrage strategy and understand difficulties in implementing index arbitrage strategy.
- Learn to create long-short portfolio strategy and understand how to refine the strategy.
- Learn about the importance of stop loss in implementing Mean Reverting strategies.
- You will get all the strategy codes in an iPython notebook.
- You will get your own Python coding environment where you can practice the codes.
- Opportunity to get certified by QuantInsti.
- Enroll once and get lifetime access to the course!
About the author
Dr. Ernest P. Chan
Ernie is the Managing Member of QTS Capital Management, LLC., a commodity pool operator and trading advisor. QTS manages a hedge fund as well as individual accounts. More information about his services can be found at . Ernie is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business” and “Algorithmic Trading: Winning Strategies and Their Rationale”, both published by John Wiley & Sons. He maintains a popular blog “Quantitative Trading” at epchan.blogspot.com.
Другие курсы от QUANTRA: https://skladchik.com/tags/quantra/
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