/financial_planning

financial planner for retirement and emergencies

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Bitcoin/Crypto Fincancial Analysis - Arbitrage Opportunities

  • This project entails building a tool to help credit union members evaluate their financial health. Specifically, members should beable to do two things:*
    1. They should be able to assess their monthly budgets.*
    1. They should be able to forecast a reasonably effective retirement plan based on their current holdings of cryptocurrencies, stocks, and bonds.*

Technologies

  • Programming Language: Python
  • Libraries: OS, Requests, JSON, Python-dotenv, MCForecastTools
  • Software Development Kit: Alpaca-Trade-API
  • Framework: JupyterLab, can also use VS Code
  • Operating Systems: Mac OS, Microsoft Windows

Installation Guide

  1. Confirm installation of libraries: "conda list requests", "conda list json"
  2. Pip install: dotenv, alpaca-trade-api
  3. Create Alpaca account to obtain your API Key and Secret Key. Both of these should be listed in a file called ".env"

Usage

Creating a plan for emergencies

Step 1: Assessing current value of the portfoloio

Step 2: Assessing emergency fund requirements

  • We have set the requirements of emergency fund to 3x the monthly income.

Creating a plan for retirement

Step 1: Collect Data

  • 3 years of portfolio returns assumming a 40-60 allocation (40% bonds and 60% stocks) using the Alpaca API

Step 2: Run simulations

  • Run a 30 year Monte Carlo Simulation to determine the range of potential portfolio returns over the next 30 years.

1_MC

2_distr

  • Run a 10 year Monte Carlo Simulation to determine the range of potential portfolio returns over the next 10 years. We chose to alter the portfolio to include a 20-80 allocation (bonds to stocks) in order to test if a more aggressive approach would shorten the time to retirement. As you can see below, the distribution is greater. I would hypothesize that this is because the asset allocation is riskier. Also, the average return is still 2.5x lower than the 30 year average expected return.

3_dist

Contributor


License

This software is licensed under GNU General Public License v3.0. See the LICENSE file for details.