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Jupyter Notebook analyzing Investment Banking Fees for Top 10 International Banks

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Investment Banking Fees for Top Ten Banks

Investment Banking

Project Title: Analysis of Top 10 Investment Banks

Team Members of Group 3: Derek P, Katie B, Cheryl Z, Kevin N, Ray H

Project Description/Outline:

Our project aims to perform a data analysis of the top 10 investment banks using various datasets and visualize the findings using Matplotlib. This project will be divided into multiple tasks, with each member focusing on a specific aspect of the project research.

Questions to Answer:

  1. What are the largest investment banks by market share and how did they trend during a five-year window?
  2. What is the size of the banks currently, based on total revenue and total assets, and how do they compare to investment banking (IB) fees?
  3. How big of a portion of these banks' non-interest income are IB fees?
  4. What do measures of central tendency and other statistics tell us about the results?

Dataset to be Used:

The team will use publicly available financial data for the top 10 investment banks, such as annual reports, financial statements, and other relevant sources. The team will also use APIs to gather additional data, such as stock prices, news articles, and analyst ratings.

Rough Breakdown of Tasks:

Data Collection and Cleaning: Will be responsible for collecting and cleaning the data using Pandas and will create a Jupyter Notebook to document the data exploration and cleanup process.

Data Analysis: Will use Pandas to perform the data analysis and create visualizations using Matplotlib and will create a Jupyter Notebook to illustrate the final data analysis.

Visualization: Will create 6 to 8 visualizations of the data, at least 2 visualizations per research question, using Matplotlib and will save PNG images of the visualizations to share with the class and instructional team.

Write-up: Will contribute to writing a summary of the major findings, including headings, for each research question, as well as a short description of the findings and relevant plots.

Bonus Task: Will use at least one API to gather additional data pertinent to the research questions.

Findings:

Where and how we found the data we used to answer these questions

To answer our questions, we obtained our data mainly from the 10-K annual reports filed with the SEC in EDGAR. The exception to this is for foreign banks that are not required to file such reports with the SEC. In those cases, we pulled the annual reports from their investor information pages after confirming the CIK# on EDGAR. We found the data by pulling the CIK#s to identify the correct 10-K reports for the corresponding banks over the past five years.

Explain your data exploration and clean-up process

Our data exploration and clean-up process posed a number of challenges. Since not all banks are located in the US, not all of them were required to submit 10-K reports to the SEC. Additionally, their Income Statement and Balance Sheet were in their local currency rather than USD, which prompted conversion involving the use of year-end spot rates. Moreover, not all of the banks filed their annual reports during the typical year-end business cycle, rather, they filed them in different months. The reports were also large and not in CSV/Excel format, requiring us to manually sift through the reports to locate the Consolidated Income Statement and Balance Sheet and extract the appropriate figures. The banks also used different names to describe similar activities within the Income Statement and Balance Sheet, in addition to formatting numbers differently (e.g., shortening them from thousands to millions), necessitating standardization to millions. Each bank had numerous legal entities, subsidiaries, and lines of business, making it challenging to ensure that we had the correct data which fed up with the parent company's consolidated statements. Furthermore, many of our group members were not familiar with financial account data, and some of the terms and concepts were difficult to understand.

  1. What are the largest investment banks by market share and how did they trend during a five-year window?

The banks ranked by market share over the 5yr aggregate are JP Morgan, Goldman Sachs, Morgan Stanley, Bank of America, Citibank, Barclays, Jefferies, Deutche Bank, Royal Bank of Canada, and Credit Suisse. Looking at the 5-year trends we can see that JP Morgan was the top IB with Goldman Sachs as second until the most recent year where Goldman Sachs overtook JP Morgan. We also found that the smallest investment banks are pretty variable with Credit Suisse at the bottom in 2017, Royal Bank of Canada in 2018, Jefferies in 2019, and now, back-to-back smallest IB bank until 2020-2021, Deutche Bank.

  1. What is the size of the banks currently, based on total revenue and total assets and how do they compare to IB fees?

The Income Statement and Balance Sheet are the major financial statements used to analyze banks. We took the current Total Revenue (Income Statement) and Total Assets (Balance Sheet) to help us compare and measure the banks. Goldman Sachs overtook JP Morgan in the most recent year for total IB fees, although JP Morgan still holds #1 in Revenue and Assets, and Goldman Sachs holds #2. We also see that even though Deutsche Bank has now been the smallest IB of the 10 investment banks for the last 2 years, in regard to Revenue they are 3rd from the bottom, in front of Credit Suisse and Jefferies, as well as middle (5th) overall in assets in front of Royal Bank of Canada, Morgan Stanley, Credit Suisse, and Jefferies.

  1. How big of a percentage of these banks' non-interest income are IB fees?

Investment banking fees make up a portion of the non-interest income which, when combined with Net interest income make up our total revenue. When we look at IB fees as a percentage of total non-interest income over the 5-yr period we see that pretty much for all of the banks that IB fees sit in the range of about 10 to 30%, whereas for Jefferies IB fees makes up about 40% to 80% of their non-interest income from Year to year. This makes sense as the majority of Jefferies income comes primarily from investment banking compared to the more diversified Income Statement for our other banks. In addition, even though JP Morgan and Goldman Sachs have bigger IB fees, their IB fee percentage is not as significant as Jefferies. We can also conclude from our findings that JP Morgan and Goldman Sachs have their assets elsewhere.

  1. What do measures of central tendency and other statistics tell us about the results?

Looking at our regression, we can see that total IB fees were increasing over the last 5-year period, though not significantly. This makes sense because when we look at overall bank size, income statement, and balance sheet for these banks, they continue to increase over the 5-year period. In other words, we can visualize that IB fees are rising with the rest of the bank's earnings and assets, as it plays a significant role in some banks' earnings.

Implications

The banks at the top of investment banking for the past half decade normally do not move much in overall market share, with more variability surrounding the lower market shares; although smaller investment bank income does not necessarily mean a smaller income statement or balance sheet.

References:

https://www.sec.gov/edgar/searchedgar/companysearch

https://home.barclays/investor-relations/reports-and-events/annual-reports/

https://investor-relations.db.com/reports-and-events/annual-reports/

https://ir.jefferies.com/financials/annual-reports/default.aspx?KeyGenPage=1073752645

https://www.credit-suisse.com/about-us/en/reports-research/annual-reports.html)

https://www.rbc.com/investor-relations/financial-information.html

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