HighFrequencyCovariance: A Julia Package for Estimating Covariance Matrices Using High Frequency Financial Data
Dublin Core
Title
HighFrequencyCovariance: A Julia Package for Estimating Covariance Matrices Using High Frequency Financial Data
Subject
covariance estimation, correlation, volatility, high frequency financial data, Julia.
Description
High frequency data typically exhibit asynchronous trading and microstructure noise,
which can bias the covariances estimated by standard estimators. While a number of
specialized estimators have been proposed, they have had limited availability in open
source software. HighFrequencyCovariance is the first Julia package which implements
specialized estimators for volatility, correlation and covariance using high frequency financial data. It also implements complementary algorithms for matrix regularization.
This paper presents the issues associated with exploiting high frequency financial data
and describes the volatility, covariance and regularization algorithms that have been implemented. We then demonstrate the use of the package using foreign exchange market
tick data to estimate the covariance of the exchange rates between different currencies.
We also perform a Monte Carlo experiment, which shows the accuracy gains that are
possible over simpler covariance estimation technique
which can bias the covariances estimated by standard estimators. While a number of
specialized estimators have been proposed, they have had limited availability in open
source software. HighFrequencyCovariance is the first Julia package which implements
specialized estimators for volatility, correlation and covariance using high frequency financial data. It also implements complementary algorithms for matrix regularization.
This paper presents the issues associated with exploiting high frequency financial data
and describes the volatility, covariance and regularization algorithms that have been implemented. We then demonstrate the use of the package using foreign exchange market
tick data to estimate the covariance of the exchange rates between different currencies.
We also perform a Monte Carlo experiment, which shows the accuracy gains that are
possible over simpler covariance estimation technique
Creator
Stuart Baumann
Source
https://www.jstatsoft.org/article/view/v103i14
Publisher
University of Oxford
Date
July 2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Stuart Baumann, “HighFrequencyCovariance: A Julia Package for Estimating Covariance Matrices Using High Frequency Financial Data,” Repository Horizon University Indonesia, accessed April 18, 2025, https://repository.horizon.ac.id/items/show/8269.