Exploring BMO Mutual Funds

by Luca Zhou

Investment is a field that requires lifelong learning, and I'd like to start earlier. The primary purpose of this project is to explore all BMO mutual funds performances data using Jupyter Notebook and build a stable portfolio for my future financial independence. This project consists of three parts:

1. Data wrangling: collect and clean the data into a playable format. If you wonder how the data collection and cleaning is done, see DataWrangling.ipynb for more detail.
2. Exploratory data analysis (EDA): supplement statistics with appropriate plots to understand the distributions and relationships. Notice that the file EDA.ipynb contains the detailed exploration process.
3. Communicate my findings: implement a dynamic dashboard for communicating insights. If you are interested in the dashboard I created using Tableau here is the link to it: BMO Mutual Funds: 1 Year Performance Heat Map.

Prerequisite

The project was built using Python 3, and the primary IDE is Jupyter Notebook. To follow along, I recommend installing the Anaconda distribution since it includes all necessary Python libraries and Jupyter Notebook. The following libraries are expected to be used in this project:

• NumPy
• Pandas
• Matplotlib
• Seaborn

Notice that in the data wrangling section, web scraping is needed. Here are the essential libraries I used for extracting and parsing web data:

• Requests: a HTTP library for making requests.
• Selenium: create a browser and act like a human. (make sure you download the driver)
• BeautifulSoup: for pulling data out of HTML and XML files.

Dataset

Since I don't have first-hand data from BMO, web scraping is needed. To know more about how I collected the data, see DataWrangling.ipynb for more detail.

The following are the cleaned datasets I wrangled from BMO:

File Name	Definition
resources/BMOMutualFunds.csv	It includes basic information about individual funds.
resources/BMOFundPrices.csv	It provides information about the fund price for a given date in the past 12 months.

The features (columns) included in the data are as follows:

resources/BMOMutualFunds.csv

Feature	Definition
Fund ID	the BMO fund ID
Fund Name	the name of the fund
Asset Class	the asset class of the fund
Assets	the assets of the fund (million)
Date Started	the created date

resources/BMOFundPrices.csv

Feature	Definition
Fund ID	the BMO fund ID
Effective Date	the date of the record
NAV	net asset value
Income
Capital Gain
Total Distribution
Reinvestment Price

Summary of Findings

Key Insights for Presentation