pyflux.com

PyFlux

Skip to Main Content. An open source time series library for the Python Programming Language. Time Series Made Easy. Built upon the NumPy/SciPy/Pandas libraries, PyFlux allows for easy application of a vast array of time series methods and inference capabilities. See worked-through examples in this talk. Given to PyData San Francisco in August 2016, or see the notebooks below for more specific examples. Long memory EGARCH models. GAS State Space models. Gaussian State Space Models.

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Skip to Main Content. An open source time series library for the Python Programming Language. Time Series Made Easy. Built upon the NumPy/SciPy/Pandas libraries, PyFlux allows for easy application of a vast array of time series methods and inference capabilities. See worked-through examples in this talk. Given to PyData San Francisco in August 2016, or see the notebooks below for more specific examples. Long memory EGARCH models. GAS State Space models. Gaussian State Space Models.

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PyFlux | pyflux.com Reviews

https://pyflux.com

Skip to Main Content. An open source time series library for the Python Programming Language. Time Series Made Easy. Built upon the NumPy/SciPy/Pandas libraries, PyFlux allows for easy application of a vast array of time series methods and inference capabilities. See worked-through examples in this talk. Given to PyData San Francisco in August 2016, or see the notebooks below for more specific examples. Long memory EGARCH models. GAS State Space models. Gaussian State Space Models.

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pyflux.com

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GAS Models – PyFlux

http://www.pyflux.com/gas-models

Skip to Main Content. Generalized Autoregressive Score (GAS) models are a recent class of observation-driven time-series model for non-normal data. For a conditional observation density. And a latent time-varying parameter. We assume the parameter. For example, for a Poisson distribution density, where the default scaling is. The time-varying parameter follows:. Types of GAS Model. PyFlux supports many types of distribution for GAS modelling, including. Poisson GAS for Banking Crisis data. Argument speci...

2

Introduction — PyFlux 0.4.0 documentation

http://www.pyflux.com/docs

Getting Started with Time Series. Dynamic Linear regression models. Beta-t-EGARCH in-mean regression models. Beta-t-EGARCH long memory models. Beta Skew-t GARCH models. Beta Skew-t in-mean GARCH models. GAS local level models. GAS local linear trend models. Gaussian Local Level models. Gaussian Local Linear Trend models. Non-Gaussian Dynamic Regression Models. Non-Gaussian Local Level Models. Non-Gaussian Local Linear Trend Models. And latent variables (parameters) (z ). The project is open source, and c...

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Skew-t-EGARCH – PyFlux

http://www.pyflux.com/skew-t-egarch

Skip to Main Content. The skew-t EGARCH model follows the same principle as Beta-t-EGARCH models, but uses the skew-t distribution of Fernandez and Steel (1998) to take into account skewness in the time series. See Harvey (2011) for the full exposition. In particular, the Fernandez and Steel (1998) method takes a continuous probability density function. That is unimodal and symmetric and constructs a skewed probability density as follows:. Latent variable represents the degree of skewness; for. And make ...

4

Philosophy – PyFlux

http://www.pyflux.com/philosophy

Skip to Main Content. PyFlux aims to make estimation. Possible in a few lines of code. To achieve this we have a simple API that carries across model types, irrespective of their complexity. This allows you to quickly perform analysis without spending too much time reading documentation. PyFlux brings modern time series models. To users. This includes score-driven models, non-Gaussian state space models and modern dynamic volatility models. PyFlux also brings modern methods of inference.

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Skew-t EGARCH-in-mean – PyFlux

http://www.pyflux.com/skew-t-egarch-in-mean

Skip to Main Content. Skew-t-EGARCH-in-mean models follow the same basis as the Beta-t-EGARCH-in-mean model, but have scores for the skew-t distribution and the skew-t distributional assumption for the residuals. First let us load some financial time series data from Yahoo Finance:. Now let’s fit the EGARCH-in-mean model with the skew-t formulation:. Skewt model = pf.SEGARCHM(p=1,q=1,data=returns,target='AAPL Returns') x = skewt model.fit() x.summary(). Skewt model.plot z([6],figsize=(15,5).

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pyflux.com

PyFlux

Skip to Main Content. An open source time series library for the Python Programming Language. Time Series Made Easy. Built upon the NumPy/SciPy/Pandas libraries, PyFlux allows for easy application of a vast array of time series methods and inference capabilities. See worked-through examples in this talk. Given to PyData San Francisco in August 2016, or see the notebooks below for more specific examples. Long memory EGARCH models. GAS State Space models. Gaussian State Space Models.

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