A Python package for high-frequency econometrics estimators
Project description
Realized Library
Realized Library is an open-source Python package for the computation of high-frequency econometrics estimators, such as variance, covariance and jump detection. It is designed as a modern, efficient, and production-ready continuation of the Oxford-Man Institute's original Realized Library.
The package focuses on performance and scalability, supporting large-scale high-frequency financial datasets (with trade, quote and time-sampled prices) up to the nanoseconds precision. The primary goal is to provide accurate, fast, and customizable estimators suitable for both academic research and quantitative analysis.
Background
This library is inspired by the Oxford-Man Institute of Quantitative Finance's original "Realized Library" (no longer maintained). It is designed for researchers, practitioners, and quantitative analysts who require fast and reliable estimations of variance, co-variance, jump and co-jumps in financial markets.
For reference to the underlying econometric methods, please consult the academic literature included in the original library or related publications in high-frequency financial econometrics. Since the website is no longer maintained, key information could be found on Wayback Machine trough this URL.
Key Features
- Efficient realized variance estimation from high-frequency price data
- Flexible resampling, subsampling and preaveraging utility with customizable parameters
- Designed for research, production pipelines, and large nanoseconds HFT datasets
Installation
pip install realized-library
Or, for development use:
git clone https://github.com/GabinTB/realized-library
cd realized-library
pip install -e .
The library requires Python 3.10.
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