Develop, test, and implement momentum trading strategies
Momentum trading is a type of trading strategy involving the purchase of assets or asset classes that have demonstrated high returns over a recent period in time, optionally accompanied by selling assets that have demonstrated poor returns over the same period in time. The basis for successful momentum trading lies in the tendency of many assets to demonstrate persistence of high or low periodic returns.
Momentum trading strategies can be categorized as:
- Absolute momentum. Also known as time-series momentum or price momentum, these strategies measure momentum by looking at individual time series in isolation.
- Cross-sectional momentum. These strategies measure and rank momentum on a relative basis across a group of time series, buying the uppermost quantiles and selling the lowermost quantiles in a market-neutral manner.
Momentum trading is closely related to other trading strategies such as trend following, and is prevalent in asset classes such as commodities or equities. Mutual funds, hedge funds, managed futures funds, and asset management firms implement momentum trading strategies to perform tactical asset allocation, optimize their portfolios, and enhance their alpha generation activities.
A practical implementation approach involves modeling, building, and testing momentum trading strategies across asset classes, using data gathered from datafeeds and databases. An effective workflow enables you to:
Create dynamic and asset allocation techniques
For more information, see MATLAB® and toolboxes for datafeed, finance, statistics, and optimization.
Examples and How To
- Workflow for Trading Technologies X_TRADER - Documentation
- Connecting to Bloomberg V3 Data Server - Documentation
- Connecting to Reuters Market Data Server - Documentation
- Technical Indicators - Documentation
- Investment Performance Metrics - Documentation
See also: commodities trading, energy trading, equity trading, financial risk management, swing trading, backtesting