The research process requires designing and selecting alpha factors with respect to the predictive power of their signals. An algorithmic trading strategy will typically build on multiple alpha factors that send signals for each asset. These factors may be aggregated using an ML model to optimize how the various signals translate into decisions about the timing and sizing of individual positions, as we will see in subsequent chapters.
Alpha factor resources
Alternative algorithmic trading libraries
Additional open-source Python libraries for algorithmic trading and data collection include (see links on GitHub):
- QuantConnect is a competitor to Quantopian
- WorldQuant offers online competition and recruits community contributors...
