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Reimplementation of Autoencoder Asset Pricing Models (GKX, 2019)

Home Page: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536

Python 100.00%
autoencoder asset-pricing

autoencoder-asset-pricing-models's Introduction

Hey! Nice to see you.

๐Ÿ“Š this week I spent my time on:

Python          8 hrs 45 mins   โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–“   98.84 %
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GIF

๐Ÿค— Iโ€™m currently pursuing my double bachelors degree of computer science and finance at Tsinghua University, Beijing.

๐ŸŽฏ Iโ€™m interested in Machine Learning, Deep Learning and their applications in quantitative finance.

โŒจ I'm frequently coding in

โš™ I'm continually using

๐Ÿ›ธ I'm familiar with

๐Ÿš€ My Contributions

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autoencoder-asset-pricing-models's Issues

Add 2023-2024 dataframe

Is this possible to have the data up-to-date with 2023-24 data ?

Thanks you a lot for the work

About the method of preprocessing

From the data_prepare.py I find that the managed portfolio is constructed using the classical method, i.e., long the first decile and short the last decile. However, the preprocessing method of GKX (2021) is a linear transformation of returns (see equation (16) in the original paper). I wonder if it is your simple choice for convenience, or you just find the classical method is better than the authors' method?

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