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Calculating companies stocks risk

This is a project calculating logarithmic rate of return and standard deviation (risk) of two companies,

  • PG - Procter & Gamble
  • BEI.DE - Beiersdorf

we are using two of the must-have python packages for Data Science and Finance:

  • NumPy : allowing us to work with multidimensional arrays, and a fast numeric array computations
  • Pandas : allowing us to organize data in a tabular form, and quickly loading remote data or a .csv file.

with this project we reinforce the fact that stocks with higher expected return, OFTEN embed MORE risks.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Docker

Installing

  1. Copy the project to your machine

    git clone https://github.com/ayoubabozer/calculating-stocks-risk.git
    
  2. Get into the Dir

    cd calculating-stocks-risk
    
  3. Build Docker

     docker build -t <tag_name> .
    
    • don't forget the dot.
  4. Run docker

       docker run -it <tag_name>
    
    • -it : to make sure that it runs in interactive mode with the terminal attached.

ENJOY!.

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