AtsPy: Automated Time Series Forecasting in Python

2 Pages Posted: 14 May 2020

See all articles by Derek Snow

Derek Snow

The Alan Turing Institute; New York University (NYU) - Finance and Risk Engineering Department; University of Auckland

Date Written: April 20, 2020

Abstract

This short report deals with the recent rise of programmatic time series methods. This decade has witnessed the proliferation of commercial and open source time-series tooling, which calls for an exposition of what is publicly available. In tandem with this survey, AtsPy, an open source automated time series framework is developed as a working prototype to showcase the ability of state of the art univariate time series methods.

Keywords: Automated Time Series, Time Series, Forecasting, Economics, Business

JEL Classification: C01, C22, C32, C53

Suggested Citation

Snow, Derek, AtsPy: Automated Time Series Forecasting in Python (April 20, 2020). Available at SSRN: https://ssrn.com/abstract=3580631 or http://dx.doi.org/10.2139/ssrn.3580631

Derek Snow (Contact Author)

The Alan Turing Institute ( email )

British Library, 96 Euston Rd
London, NW1 2DB
United Kingdom

HOME PAGE: http://https://www.turing.ac.uk/

New York University (NYU) - Finance and Risk Engineering Department ( email )

6 Metrotech Center
New York, NY 11201
United States

University of Auckland ( email )

Private Bag 92019
Auckland Mail Centre
Auckland, 1142
New Zealand

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