MicrostructureNoise.jl
Description
MicrostructureNoise is a Julia package for Bayesian volatility estimation in presence of market microstructure noise. The estimation methodology is intuitive to understand, given that its ingredients are well-known statistical techniques. The posterior inference is performed via the Gibbs sampler, with the Forward Filtering Backward Simulation algorithm used to reconstruct unobservable states.
See https://mschauer.github.io/MicrostructureNoise.jl/latest for the documentation.
References
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Shota Gugushvili, Frank van der Meulen, Moritz Schauer, and Peter Spreij: Nonparametric Bayesian volatility estimation. arxiv:1801.09956, 2018.
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Shota Gugushvili, Frank van der Meulen, Moritz Schauer, and Peter Spreij: Nonparametric Bayesian volatility learning under microstructure noise. In preparation.
Files
mschauer/MicrostructureNoise.jl-v0.9.0.zip
Files
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Additional details
Related works
- Is supplement to
- https://github.com/mschauer/MicrostructureNoise.jl/tree/v0.9.0 (URL)