This is a pandas-based technical analysis library and financial feature engineering tool. It serves as a vectorized indicator calculator that transforms raw price and volume data into derived metrics for time series analysis.
The library uses a NumPy-based engine to perform mathematical operations across entire arrays, avoiding iterative loops to maintain high performance. It organizes technical indicators into a modular class hierarchy with a consistent interface, allowing for bulk feature generation and the direct appending of results as new columns to a pandas DataFrame.
The system covers a wide range of financial metrics, including momentum oscillators, asset return metrics, and trend direction indicators. It also provides tools for measuring volatility through statistical bands and analyzing market pressure via volume-weighted metrics.
To ensure dataset completeness for machine learning, the processor includes configurable strategies for filling missing values and allows for the tuning of indicator parameters such as moving average periods.