Metadata-Version: 2.1
Name: webappPP
Version: 1.1.1
Summary: Algorithm for finance
Home-page: UNKNOWN
License: MIT
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: pandas-datareader
Requires-Dist: scipy
Requires-Dist: Flask
Requires-Dist: seaborn

This package has multiple purposes.

Covid Resilience :

The first purpose of the package is, given a list of stock tickers is to state what are the most covid resilient stocks and what are the worst ones.
It computes a very simple score based on the volatility and return of the stocks over different periods.


CovidResilience(stock_index = "STOXX 600", start_date = None, end_date = None, tickers = None)


Input: 

- stock_index : benchmark  (example : "CAC 40","S&P 500", "STOXX 600")
- start_date, end_date : strings, format "YYYY-MM-DD"
- tickers : list of tickers
ex : CovidResilience("STOXX 600","2020-01-19", "2021-01-19", tickers = list_of_tickers)


Output:

- .relevant_data
- .relevant_data_returns
- .volatilities
- .rslt


Example (copy/paste):

!pip install FINANCEPP

from finance import covidresilient as cr

list_of_tickers = ["FP.PA","MC.PA","AI.PA","OR.PA", "RI.PA","AIR.PA"]

covidfilter = cr.CovidResilience("CAC 40","2020-01-19", "2021-01-19", tickers = list_of_tickers)

covidfilter.run()

covidfilter.rslt

