Momentum Trading Strategies by Quantra Quantinsti instructs you on developing time-series and cross-sectional momentum strategies. Trading instruments that you can apply the frameworks include stocks, stock indexes, fixed income, and futures.
Momentum Trading Strategies by Quantra Quantinsti will help you create time-series and cross-sectional momentum strategies for stocks, stock indexes, fixed income, and futures contracts. You can learn how to evaluate time series, portfolio returns, and risks statistically. It also addresses how to construct and backtest momentum trading strategies.
- Introduction to the course
- What is momentum?
- Why does momentum exist?
- Introduction to python
- Financial market data and visualization
- Technical indicators
- Technical indicator strategy
- Live trading on blueshift
- Live trading template
- Types of momentum
- Time-series momentum
- Hurst exponent
- Correlation analysis
- Cross-sectional momentum
- Fundamental momentum
- Event-driven strategy
- Ranking factors for cross-sectional portfolio
- Treasury markets
- Momentum in futures
- Cross-sectional momentum strategy in futures
- Momentum crashes
- Automate trading strategies
- Risk management
- Python installation
- Course summary
What Will You Learn?
- Incorporate time series and cross-sectional momentum methods into stock, stock indexes, fixed income, and commodities futures.
- A solid grounding in time-series analysis of portfolio returns, risks, and momentum trading techniques.
- Understanding why momentum trading tactics can consistently outperform other trading methods.
- Stock, stock indices, fixed income, commodities, and futures markets can serve as testing grounds for developing and testing momentum strategies.
- Using a variety of performance metrics to examine the portfolio’s returns and risks.
- Determining a time series’ type, one may apply the Hurst exponent to it.
- Conveying futures market principles such as contango, backwardation, term structure & roll returns.
- Volatility decile portfolios should be subjected to crossover and breakout modeling.
- Using Blueshift, you may trade on paper, evaluate the results, and then execute your trades in real-time on the market.
Who Is This Course For?
The course assumes that students have a working knowledge of financial markets, including the buying and selling of stocks. Also, it needs a working grasp of equity, ETF, and futures markets.
The principles presented in this course may be acquired without a prior understanding of programming. To execute the tactics discussed, you must have a working knowledge of pandas and matplotlib.
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