Latent_Factors_in_Stocks

Latent_Factors_in_Stocks

at-tan

Dynamic factor modeling to uncover the key latent factors driving the price behavior of some of the largest American large-cap equities. We examine how these factors affect individual stock prices, what they represent, and how they have fluctuated in the sample period. As published in the Data Driven Investor on Medium.com.

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7 Watchers
Jupyter Notebook Language
Cost to Build
$31.1K
Market Value
$19.6K

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1 data points  ·  2022-09-24 → 2022-09-24
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What is the at-tan/Latent_Factors_in_Stocks GitHub project? Description: "Dynamic factor modeling to uncover the key latent factors driving the price behavior of some of the largest American large-cap equities. We examine how these factors affect individual stock prices, what they represent, and how they have fluctuated in the sample period. As published in the Data Driven Investor on Medium.com.". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

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