ARCHModels.jl: Estimating ARCH Models in Julia
This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the conditional volatility of financial assets. The dis...
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2023-09-01
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| Series: | Journal of Statistical Software |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/4714 |
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| _version_ | 1846101673627353088 |
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| author | Simon A. Broda Marc S. Paolella |
| author_facet | Simon A. Broda Marc S. Paolella |
| author_sort | Simon A. Broda |
| collection | DOAJ |
| description |
This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the conditional volatility of financial assets. The distinguishing feature of these models is that they model the latent volatility as a (deterministic) function of past returns and volatilities. This recursive structure results in loop-heavy code which, due to its just-in-time compiler, Julia is well-equipped to handle. As such, the entire package is written in Julia, without any binary dependencies. We benchmark the performance of ARCHModels.jl against popular implementations in MATLAB, R, and Python, and illustrate its use in a detailed case study.
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| format | Article |
| id | doaj-art-0b30bb9068d6412ea595b7eccbe7f71b |
| institution | Kabale University |
| issn | 1548-7660 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Foundation for Open Access Statistics |
| record_format | Article |
| series | Journal of Statistical Software |
| spelling | doaj-art-0b30bb9068d6412ea595b7eccbe7f71b2024-12-29T00:12:48ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602023-09-01107110.18637/jss.v107.i05ARCHModels.jl: Estimating ARCH Models in JuliaSimon A. Broda0Marc S. Paolella1Lucerne University of Applied Sciences and ArtsUniversity of Zurich This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the conditional volatility of financial assets. The distinguishing feature of these models is that they model the latent volatility as a (deterministic) function of past returns and volatilities. This recursive structure results in loop-heavy code which, due to its just-in-time compiler, Julia is well-equipped to handle. As such, the entire package is written in Julia, without any binary dependencies. We benchmark the performance of ARCHModels.jl against popular implementations in MATLAB, R, and Python, and illustrate its use in a detailed case study. https://www.jstatsoft.org/index.php/jss/article/view/4714 |
| spellingShingle | Simon A. Broda Marc S. Paolella ARCHModels.jl: Estimating ARCH Models in Julia Journal of Statistical Software |
| title | ARCHModels.jl: Estimating ARCH Models in Julia |
| title_full | ARCHModels.jl: Estimating ARCH Models in Julia |
| title_fullStr | ARCHModels.jl: Estimating ARCH Models in Julia |
| title_full_unstemmed | ARCHModels.jl: Estimating ARCH Models in Julia |
| title_short | ARCHModels.jl: Estimating ARCH Models in Julia |
| title_sort | archmodels jl estimating arch models in julia |
| url | https://www.jstatsoft.org/index.php/jss/article/view/4714 |
| work_keys_str_mv | AT simonabroda archmodelsjlestimatingarchmodelsinjulia AT marcspaolella archmodelsjlestimatingarchmodelsinjulia |