1. Introduction
2. Project Overview
3. Questions addressed
4. File Description
5. Dataset Overview
6. Acknowledgements

In this project:

• I have analyzed real life data from the New York Stock Exchange.
• I’ll be drawing a subset of a large dataset provided by Kaggle that contains historical financial data from S&P 500 companies.
• I have created a smaller subset of the data that I will be using for the project using the Fundamentals.csv and Securities.csv files provided by Kaggle.
• Summary statistics and insights is performed for 3 banks
• P&L statement and Financial forecast can be performed for all the companies

• Developed a dynamic Profit and Loss Dashboard that calculates the Gross Profit, Total Operating Expenses and Operating Profit or EBIT for a company selected from a drop-down list
• Created a dynamic Financial Forecasting Model including forecasts for Revenue, Gross Profit and Operating Profit for two more years using scenario analysis to forecast future growth prospects for the company
• Calculated summary statistics including measures of center and spread for the financial business metrics in the Financial GICS sector for Banks GICS sub-category
• Drew inference from the statistical to create visual tools to communicate the results in informative ways

1. What portion of revenue is able to cover operating expenses generated by the banks?
2. Which bank generates more Total revenue each year?
3. Do the 3 banks have similar spread in their Total Revenue and Total Operating Expenses?

• The spreadsheet file includes:
  1. Data file
  2. Summary statistics
  3. P&L Statement Dashboard
  4. Forecast Scenarios
  5. Visualization plots
• Presentation (PDF)
  1. Visualization plots
  2. Insights

• Background
  1. The Fundamentals file provides the fundamental financial data gathered from SEC 10K annual filings from 448 companies listed on the S&P 500 index
  2. The Securities file provided the industry or sector information the companies are categorized under on the S&P 500 index
• Attribute Information for the NYSE dataset:
  1. Ticker symbol: Stock symbol
  2. Years: Number of years for which data is provided
  3. Period ending
  4. Total revenue
  5. Cost of goods sold
  6. Sales, General and Administrative expenses
  7. Research and Development expenses
  8. Other Operating expense items
  9. Global Industry Classification Standard (GICS) Sector: Industry sector the company is categorized under (e.g., American Airlines with the ticker symbol AAL is categorized under Industrials.)
  10. GICS Sub Industry: Sub-industry sector the company is categorized under (e.g., AAL is further categorized under the sub-category of Airlines industry.)

The dataset files can be found here.