Quantra – Momentum Trading Strategies
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Create time series and cross sectional momentum strategies on stock, stock indices, fixed income, and commodities futures. Learn to quantitatively analyze time series, portfolio returns and risks, and design and backtest momentum trading systems.
PREREQUISITES
This course requires a basic understanding of financial markets such as buying and selling of securities. And basic knowledge of trading in equities, ETFs and futures markets. The concepts covered in this course can be learned without programming knowledge. If you want to implement the strategies covered, the basic knowledge of “pandas dataframe” and “matplotlib” is required. The required skills are covered in the free course, “Python for Trading: Basic”, on Quantra.
AFTER THIS COURSE YOU’LL BE ABLE TO
List and explain the fundamental reasons behind the significant and persistent returns from momentum trading strategies
Create and backtest time series and cross sectional momentum strategies on stock, stock indices, fixed income, and commodities futures
Optimise look back and holding period
Analyse portfolio returns and risk using different performance measures
Identify the nature of time series using Hurst exponent
Explain the basic concepts in futures markets such as contango, backwardation, term structure and roll returns
Apply crossover and breakout models to volatility decile portfolio
SYLLABUS
Introduction to the Course
What is Momentum?
Why Does Momentum Exist?
Introduction to Python
Technical Indicator
Technical Indicator Strategy
Types of Momentum
Time Series Momentum
Hurst Exponent
Correlation Analysis
Cross Sectional Momentum
Fundamental Momentum
Ranking Factors for Cross Sectional Portfolio
Event Driven Strategy
Treasury Markets
Momentum in Futures
Cross Sectional Momentum Strategy in Future
Momentum Crashes
Risk Management
Automate Trading Strategies
Python Installation
Course Summary
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