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Machine learning methods for identifing investment factors

Jupyter Notebook 100.00%
machine-learning stock-market python jupiter-notebook deep-learning

empirical-asset-pricing-via-machine-learning-evidence-from-the-german-stock-market's Introduction

Empirical Asset Pricing via Machine Learning: Evidence from the German Stock Market

References:

Gu, Shihao; Kelly, Bryan; Xiu, Dacheng (2020): Empirical asset pricing via machine learning, in: The Review of Financial Studies, Vol. 33.5, S. 2223-2273.

empirical-asset-pricing-via-machine-learning-evidence-from-the-german-stock-market's People

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empirical-asset-pricing-via-machine-learning-evidence-from-the-german-stock-market's Issues

Data for the notebooks

Thank you for providing the code here for free!

I read the paper (Empirical Asset Pricing via Machine Learning, Gu et al.,2020) and would like to experiment with your code. I'm a Ph.D. student in the field of natural language processing (NLP), and would like to write a paper about how to incorporate NLP data into the Gu et al. (2020) methods.

Would it be possible to share the code? That would be very helpful. Thank you.

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