Unit 5 — How do you like them apps?

Background

The Consumer Division of Harold's company has decided to offer budgeting and financial planning services to customers. They want to build a report for customers that links to their banking and investment accounts and automatically refreshes the data and charts on login. However, some of the calculations are tricky, and Harold could really use some help connecting the accounts and simulating the retirement investment projections. Luckily, there are APIs available to obtain account transactions and fetch retirement portfolio prices.

In this homework assignment, you will help Harold complete the following tasks:

Budget Analysis with Plaid
Retirement Planner
Financial Report

Files

Instructions

Note: The data produced from the api calls will vary depending on the dates used, causing results that vary from those pictured.

Budget Analysis

In this section, you will use the Plaid API to obtain transaction and account data for the budget analysis section of the report.

Follow the steps outlined in the budget starter notebook (account_summary.ipynb) to complete the following:

Generate a Plaid access token to access the Developer Sandbox.
Use the Access token to fetch account transactions from the sandbox. You should fetch the last 90 days of transactions from the sandbox using the following institution:
```
INSTITUTION_ID = "ins_109508"
```
Perform basic budget analysis on the sandbox transaction and generate the following plots:
- Spending Categories Pie Chart.
- Spending Per Month Bar Chart.
Use the API to fetch income data from the sandbox and print the following:

Last Year's Income Before Tax.
Current Monthly Income.
Projected Year's Income Before Tax.

Retirement Planner

In this section, you will use the Alpaca API to fetch historical closing prices for a retirement portfolio and then run Monte Carlo simulations to project the portfolio performance at 30 years. You will then use the Monte Carlo data to answer questions about the portfolio.

Follow the steps outlined in the budget starter notebook to complete the following:

Monte Carlo Simulation

Create a Monte Carlo simulation for the retirement portfolio:

Use the Alpaca API to fetch historical closing prices for a traditional 60/40 portfolio using the SPY and AGG tickers to represent the 60% stocks (SPY) and 40% bonds (AGG).
Run a Monte Carlo Simulation of 500 runs and 30 years for the 60/40 portfolio and plot the results.
Select the ending cumulative returns from the Monte Carlo simulation and calculate the interval values for a 90% confidence interval.
Using the ending cumulative returns, plot a histogram of the results and plot the 90% confidence interval as vertical lines on the histogram.

Retirement Analysis

Use the Monte Carlo simulation data to answer the following questions:

What are the expected cumulative returns at 30 years for the 10th, 50th, and 90th percentiles?
Given an initial investment of $20,000, what is the expected return in dollars at the 10th, 50th, and 90th percentiles?
Given the current projected annual income from the Plaid analysis, will a 4% withdrawal rate meet or exceed that value at the 10th percentile? Note: This is basically determining if retirement income is equivalent to current income.
How would a 50% increase in the initial investment amount affect the 4% retirement withdrawal? In other words, what happens if the initial investment had been bigger?
(Optional Challenge) Use the Monte Carlo data and calculate the cumulative returns at the 5%, 50%, and 95% quartiles and plot this data as a line chart to see how the cumulative returns change over the life of the investment.

Financial Report

In this section, you will compile a financial report to demo your calculations to the Consumer App Team. The report should be written as a markdown file and include the following sections:

Budget Analysis: Summarize the transaction data from the budget analysis and include images for each chart and table produced.
Retirement Planning: Summarize the retirement portfolio analysis and include the charts for the Monte Carlo simulation.

Optional Challenge — Early Retirement

Harold was really impressed with your work on this planner, but commented that 30 years seems like such a long time to wait to retire! Harold starts wondering if the retirement plan could be adjusted to retire earlier than normal. Try adjusting the portfolio to either include more risk (a higher stock than bond ratio) or to have a larger initial investment and rerun the retirement analysis to see what it would take to retire in 5 years instead of 30!

Resources

Hints and Considerations

For the Monte Carlo simulation, start out by running 100 simulations for one year of returns, and when you have the code worked out, run the simulation at 100–500 simulations for 30 years (this takes a long time).

Submission

Create Jupyter Notebooks for the analysis and planner and host the notebooks on GitHub.
Include a Markdown Financial Planner report that summarizes your assumptions and findings and include this report in your GitHub repo.
Submit the link to your GitHub project to Bootcampspot.

machkev/05-APIs-How-do-you-like-them-apps