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Dr. Ernest P Chan – Mean Reversion Strategies In Python

Name: Dr. Ernest P Chan – Mean Reversion Strategies In Python
SKU: 28042
Price: 35.00 USD
Availability: InStock

$35.00

Sale Page : quantra

Category: Forex Trading Courses

Description

Dr. Ernest P Chan – Mean Reversion Strategies In Python

Sale Page : quantra

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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.

SKILLS COVERED

Mean Reversion Strategies
- Statistical Arbitrage
- Triplets Trading
- Index Arbitrage
- Long-short strategy
Math Concepts
- Correlation, Co-integration
- Stationarity
- Linear Regression
- ADF and Johansen Test
- Half Life
Python
- Adfuller,
- Statstools,
- Johansen,
- NumPy, Pandas,
- Matplotlib

PREREQUISITES

It is expected that you have some trading experience and understand basic financial markets terminology like sell, buy, margin, entry, exit positions. Some familiarity with t-statistics and autoregressive model is useful but not mandatory. If you want to be able to code strategies in Python, then experience to store, visualise and manage data using Pandas DataFrame is required. These skills are covered in our course ‘Python for Trading’.

AFTER THIS COURSE YOU’LL BE ABLE TO

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

ABOUT AUTHOR

Dr. Ernest P. Chan

Dr. Ernest Chan 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. He has worked in IBM human language technologies group where he developed natural language processing system which was ranked 7th globally in the defense advanced research project competition. He also worked with Morgan Stanley’s Artificial intelligence and data mining group where he developed trading strategies.

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