Identification and validation of Alpha is the most important element that distinguishes portfolio managers. When seeking for Alpha, one should be aware to see the difference between market expectations and their own expectations of Alpha. Thus, it is important to implement processes that will continuously challenge and validate a professional's strategies and hypothesis.
Investors are adopting machine learning as a strategy to identify alpha and gain market advantage through sentiment analysis, alternative data insights and maximizing gains. However, the implementation of a professional’s analytical skills and moral values are important in the decision-making processes.
It is predicted that by the end of 2025, we will have 175 ZB of data. This data could be very beneficial in grasping the right trading signals, and Alpha, if filtered correctly. Thus, it is important to implement backtesting as a strategy of filtering Alpha. However, when doing so, one should take into consideration the traps of backtesting and other limitations.