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!.