d33pk3rn3l / Swiss-Interest-Calculator

This repository contains a Python script for comparing bank account returns over a year, considering different initial amounts and Effective Annual Rates (EAR). It visualizes results with matplotlib and Plotly, offering flexibility to add/remove accounts and tiers.

This Python script calculates the Effective Annual Rate (EAR) for different bank accounts and visualizes the total return after one year for a range of initial amounts. The script uses both matplotlib and plotly for visualization. Currently it outputs some Neobanks with great offers to the Swiss Public.

Code Overview

The script is divided into several functions:

• calculate_ear(i, n, t=1): Calculates the EAR given an interest rate i, number of compounding periods n, and time t.
• calculate_return(amount, ear_tiers): Calculates the total return for a given amount and a list of EAR tiers.
• calculate_returns_for_all_amounts(initial_amounts, ear_tiers): Calculates the total returns for a list of initial amounts and a list of EAR tiers.
• calculate_ear_vectorized(i, n, t=1): Vectorized version of calculate_ear for arrays.
• calculate_return_vectorized(amounts, ear_tiers): Vectorized calculation of returns for a range of amounts.
• create_and_show_figure(initial_amounts, accounts, colors): Creates a matplotlib figure and shows it.
• create_and_show_figure_plotly(initial_amounts, accounts, colors): Creates a plotly figure and saves it as an HTML file.

The script then defines a range of initial amounts and EAR tiers for each account, and uses the above functions to calculate the total return for each account and visualize the results.

Usage

To use this script, you need to have numpy, matplotlib, and plotly installed in your Python environment. You can then run the script in a Jupyter notebook or any Python environment.

Customization

You can customize the script by modifying the accounts dictionary to add or remove accounts and their EAR tiers, and the colors dictionary to change the colors used in the plots.

Output

The script outputs a matplotlib figure and a plotly figure, both showing the total return after one year for each account for a range of initial amounts. The matplotlib figure is saved as 'total_return.png', and the plotly figure is saved as 'total_return.html'.

For December 2023 the following figure is valid:

So wiLLbe is the best until you reach around 62k, then you can use Radicant for up to 250k, and after that Alpian offers 1.5% up to 1 million... You can also go to the interactive Plotly Plot to check out everything.

License

This project is licensed under The Unlicense.