Mean Reversion Strategies In Python – Dr. Ernest P. Chan-Quantinsti

Original price was: $212.00.Current price is: $72.00.

Mean Reversion Strategies In Python – Dr. Ernest P. Chan-Quantinsti

Original price was: $212.00.Current price is: $72.00.

Offered by Dr. Ernest P Chan, this course will teach you to identify trading opportunities based on Mean Reversion theory.

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Offered by Dr. Ernest P Chan, this course will teach you to identify trading opportunities based on Mean Reversion theory. You will create different mean reversion strategies such as Index Arbitrage, Long-short portfolio using market data and advanced statistical concepts. A must-do course for quant traders.

APPLY MEAN REVERSION STRATEGIES

Create four different types of mean reverting strategies
Perform statistical test for identifying stationarity and co-integration
Backtest pairs trading, triplets, index arbitrage and long-short strategy
Explain the role of risk management
Paper trade and live trade your strategies without any installations or downloads

Introduction to the Course

This section gives an overview of the mean reversion strategy through examples. You will go through the course structure and understand how the course is structured in videos, quizzes, strategy codes and interactive coding exercises. This will make sure that not only do you understand the mechanics of mean reversion but also implement trading strategies in live markets.

Introduction by Dr. Ernest Chan

Introduction to Mean Reversion Strategy

Course Structure Flow Diagram

Quantra Features and Guidance

Types of Statistical Arbitrage Strategies

Stationarity of Time Series

Stationary is one of the essential concepts upon which pairs trading and other cointegrated trading is built. This section discusses the concept of stationary through real price data and how it is different from the random walk.

What is Stationarity?

Mean Reversion Trading Approach

Temporary Mean Reversion

Stationarity

Statistical Test for Stationarity

Augmented Dickey-Fuller Test

This section covers the concept of the augmented dickey-fuller (ADF) test, which is used to check whether the price series is stationary or not. You will learn the mathematics behind the ADF test. You will also learn to check the stationarity of currency pairs in Python.

Pre Reading Materials

What is ADF Test?

Purpose of ADF Test

ADF Test Assumption

Null Hypothesis

Stationary Price Series

Math Behind ADF Test (Optional)

Critical Value and Test Statistics

How to Use Jupyter Notebook?

ADF Test on CADUSD Pair

Calculate Test Statistics

Import Library and Read CSV

Additional Reading

Frequently Asked Questions

Mean Reversion Strategy

In this section, you will learn to create and backtest a trading strategy based on the concept of mean reversion. You will learn to use the Bollinger Bands to create a mean reversion strategy on a currency pair.

Mean Reversion Strategy

Upper Band

Trading Based on Mean Reversion

Mean Reversion Strategy on AUDCAD

Calculate Moving Average and Standard Deviation

Upper and Lower Band

Long Entry and Exit

Short Entry and Exit

Long and Short Positions

Forward Fill Missing Positions

Consolidate the Positions

Compute PnL

Recap

Frequently Asked Questions

Test on Mean Reversion

Live Trading on Blueshift

This section will walk you through the steps involved in taking your trading strategy live. You will learn about backtesting and live trading platform, Blueshift. You will learn about code structure, various functions used to create a strategy and finally, paper or live trade on Blueshift.

Section Overview

Live Trading Overview

Vectorised vs Event Driven

Process in Live Trading

Real-Time Data Source

Blueshift Code Structure

Important API Methods

Schedule Strategy Logic

Fetch Historical Data

Place Orders

Backtest and Live Trade on Blueshift

Additional Reading

Blueshift Data FAQs

Live Trading Template

In this section, a live trading strategy template will be provided to you. The template strategy will be on the mean reversion strategy covered in the previous section. You can tweak the code by changing different currency pairs, date range to backtest and finally analyse the strategy performance in more detail.

Paper/Live Trading FX Mean Reversion Strategy

FAQs for Live Trading on Blueshift

Cointegration

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If a linear combination of two or more price series is stationary, then the individual price series are said to be cointegrated with each other. This section introduces cointegration between two-time series and covers a test for detecting cointegration of a portfolio of instruments called the cointegrated augmented Dickey-Fuller (CADF) test.

What is Cointegration?

Cointegration

Correlation

What is Hedge Ratio?

Portfolio Formation Using Hedge Ratio

Hedge Ratio Code

Import Library

Calculate Hedge Ratio

What is CADF Test?

Check Cointegration using CADF Test

Order Dependence of CADF

Pairs Trading

Most financial instruments are not stationary, and creating a mean reversion strategy is not possible on such a price series. To overcome this issue, you need two price series which are cointegrated with each other. In this section, you will learn to create a pairs trading strategy using the Bollinger Bands. You will also learn to backtest the same in Python.

Mean Reversion Strategy on Pairs

Mean Reversion Strategy on GLD-GDX

Take Long Entry and Exit

Compute Strategy PnL

Paper/Live Trading Pair Trading Strategy

Additional Reading

Recap

Mean Reversion Strategy

Triplets

This section discusses failure of the mean reversion strategy of the GLD-GDX pair. Based on the possible reason we will arrive at the conclusion of choosing a triplet to improve the mean reversion strategy. The working of Johansen test will be explained to arrive at the hedge ratios for the new mean reversion strategy for triplets. This section also covers the concept of half-life of mean reversion along with Ornstein-Uhlenbeck formula for computing the half-life of mean reversion.

Cointegration Breakdown in the GLD-GDX Pair

Reason of Breakdown of Cointegration

Significance of Cointegration

Surviving Breakdown of Cointegration

How to Survive Breakdown of Cointegration?

Breakdown Remedies

Optimization Problems

Eigenvalues and Eigenvectors

What is Johansen Test?

CADF Shortcomings

Linear Combination

GLD-GDX Cointegration Test

Mean Reversion on Triplets

Mean Reversion on Triplets Code

GLD-GDX-USO Cointegration Test

Cointegration Test

Taking Positions

Recap

Frequently Asked Questions

Half Life

This section explains how long would it it take for the time series to revert back to the mean. And the importance of half-life to select the right instruments to trade in.

Half Life of Mean Reverting Time Series

Half Life

Half Life Formula

Half-Life Using Johansen Test

Compute Half-Life of GLD-GDX

Frequently Asked Questions

Risk Management

This section explains the importance and two common usages of stop loss in mean reverting strategies. Further, you will learn to backtest mean-reverting strategy with and without stop and compare the performance of the strategy.

Stop-Loss

Mean Reversion Strategy With Stop Loss

Best Markets to Pair Trade

This section explains the pros and cons of mean reversion strategies in different markets such as exchange traded funds (ETFs), stocks, currencies, and futures. Further, in the section, will understand how economically related pairs do not co-integrate, cover the basic concept of crack spread and test for stationarity of crack spread.

Best Markets To Pair Trade

Mean Reversion of ETF Pairs

Mean Reversion of Stock Pairs

Mean Reversion of Currencies and Futures

Cointegration Test of CL and BZ

Cointegration Test of Crack Spread

Identify Cointegrated Stock Pairs

Index Arbitrage

This section explains Index Arbitrage Strategy which is an extension of pairs and triplets, how to construct a basket of instruments and see the difficulties of trading an Index Arbitrage strategy.

Index Arbitrage Strategy

Working of Index Arbitrage Strategy

Custom Basket

Index Arbitrage Strategy Code

Difficulties in Index Arbitrage

Long Short Portfolio

This section explains the concept of long-short portfolio strategy, how it is different from other mean reversion strategies. Further, will construct a long-short portfolio of stocks in the S&P 500, understand the importance of universe selection of stocks on strategy and learn to refine a strategy.

Long-Short portfolio Strategy

Long-Short Portfolio

Strategy Formula

Long-Short Portfolio Strategy Code

Calculate Stock Returns

Calculate Market Returns

Calculate Dollar Allocation for Each Stock

Calculate Sharpe Ratio

Paper/Live Trading Long-Short Strategy

Analysis of Strategy Performance

Test on Trading Based on Mean Reversion

Run Codes Locally on Your Machine

Learn to install the Python environment in your local machine.

Python Installation Overview

Flow Diagram

Install Anaconda on Windows

Install Anaconda on Mac

Know your Current Environment

Troubleshooting Anaconda Installation Problems

Creating a Python Environment

Changing Environments

Quantra Environment

Troubleshooting Tips For Setting Up Environment

How to Run Files in Downloadable Section?

Troubleshooting For Running Files in Downloadable Section

Automated Trading Using IBridgePy

A live trading strategy template will be provided to you. You can tweak the template to deploy your strategies on Interactive Brokers using IBridgePy API.

Additional Reading

Sample Strategy to Run on Interactive Brokers

Summary

Course Summary

Python Codes and Data

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