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Playing with different time series methods on the US stocks’ dataset with 200+ financial indicators

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Time Series Analysis

Playing with 4 different time series methods on the US stocks’ dataset with 200+ financial indicators:

US stocks’ dataset consisted of 200+ financial indicators released in 10-K filings and the goal was to predict whether a stock is worth buying given a positive price variance during 2014-2018

Made predictions on 2019 and 2020

Methods

  • Auto Regression
  • Moving Average
  • Autoregressive Moving Average
  • Autoregressive Integrated Moving Average

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Playing with different time series methods on the US stocks’ dataset with 200+ financial indicators

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