Worried about "Noisy Factors?" no need to worry any more. openassetpricing makes it easy to download any vintage of the dataset and compare:
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Peng Li
This package is the excellent work of
Peng Li
(researchportal.bath.ac.uk/en/persons/p...). I just contributed the examples, with help of Patrick Dunn.
Of course, the Chen-Zimmermann dataset would not have been possible without Tom Zimmermann.
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π₯Introducing openassetpricing!π₯ a Python package for easy-breezy access to the Open Source Asset Pricing dataset. Just `pip install openassetpricing` and
openap = oap.OpenAP()
df = openap.dl_port('quintiles_vw', 'pandas', ['BM', 'Mom12m'])
and you've got B/M and momentum.
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βAI Safetyβ is totally a law and economics topic isnβt it?
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