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.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- Docker
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Copy the project to your machine
git clone https://github.com/ayoubabozer/calculating-stocks-risk.git
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Get into the Dir
cd calculating-stocks-risk
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Build Docker
docker build -t <tag_name> .
- don't forget the dot.
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Run docker
docker run -it <tag_name>
- -it : to make sure that it runs in interactive mode with the terminal attached.