petepetersen423/m5_challenge

Module 5 Challenge

Working with Alpaca API's a

THis project inclused two financial analysis tools by using a single Jupyter notebook:

1. A financial planner for emergencies. The members will be able to use this tool to visualize their current savings. The members can then determine if they have enough reserves for an emergency fund.

2. A financial planner for retirement. This tool will forecast the performance of their retirement portfolio in 30 years. To do this, the tool will make an Alpaca API call via the Alpaca SDK to get historical price data for use in Monte Carlo simulations.

Section I - Evaluate the Cryptocurrency Wallet by Using the Requests Library

In this section, determine the current value of a member’s cryptocurrency wallet. You’ll collect the current prices for the Bitcoin and Ethereum cryptocurrencies by using the Python Requests library. For the prototype, assume that the member holds the 1.2 Bitcoins (BTC) and 5.3 Ethereum coins (ETH).

Section II - Evaluate the Stock and Bond Holdings by Using the Alpaca SDK

In this section, determine the current value of a member’s stock and bond holdings. Make an API call to Alpaca via the Alpaca SDK to get the current closing prices of the SPDR S&P 500 ETF Trust (ticker: SPY) and of the iShares Core US Aggregate Bond ETF (ticker: AGG). For the prototype, assume that the member holds 110 shares of SPY, which represents the stock portion of their portfolio, and 200 shares of AGG, which represents the bond portion.

Section III - Evaluate the Emergency Fund

In this section, use the valuations for the cryptocurrency wallet and for the stock and bond portions of the portfolio to determine if the credit union member has enough savings to build an emergency fund into their financial plan.

Section IV Create the Monte Carlo Simulation

In this section, use the MCForecastTools library to create a Monte Carlo simulation for the member’s savings portfolio. To do this, complete the following steps:

Make an API call via the Alpaca SDK to get 3 years of historical closing prices for a traditional 60/40 portfolio split: 60% stocks (SPY) and 40% bonds (AGG).

Run a Monte Carlo simulation of 500 samples and 30 years for the 60/40 portfolio, and then plot the results. The following image shows the overlay line plot resulting from a simulation with these characteristics. However, because a random number generator is used to run each live Monte Carlo simulation, your image will differ slightly from this exact image:

NOTE: Text in the readme is extracted from Module 5 challenge rubrik.