We have the ability to produce thousands of data factors in a very short time based on huge amount of IT engineering work, including various factor types and time periods.
Engineering
Combine sub-models into one final model which will go through an optimization process which balances predicted returns, risk, and trading costs.
The data processing stage lays the cornerstone for the subsequent research framework.
Engineers build AI Models, use massive amounts of data to train and ultimately obtain predicted value.
Unique way to split historical data, to prevent over-fitting.