Parse Mutual Fund Holdings

Coding Challenge

Parse mutual fund holdings by scraping the latest 13F xml file and generate a .tsv file.

How to Run

First of all, make sure we are upgraded to python 3 and pip3 and all dependencies are installed

Navigate to the ScrapeMutualFund directory and run ./main.py. We will now be asked to input a central index key (CIK) or ticker. If we enter a valid CIK/ticker that has 13F reports filed in edgar, the program will generate a .tsv file from the xml.

Will not work for funds without 13 F reports filed

External Dependencies

• requests
• BeautifulSoup
• re
• csv

Testing

I included a list of 40000+ mutual fund tickers (MutualFundSymbols.txt) and a lot of them don't have 13F reports filed, so its useful to know which mutual funds do have 13F reports filed before hand.

Goals

How we could get previous reports? When using the BeautifulSoup parser, we can use the find_all method to return a list of tags, in this case it we would be looking for the documents button. Once we have the list of tags, we can specify which one we want to use by choosing an index of the tag list.

Thoughts on how to deal with different formats. When scraping the xml I choose not to explicitly define the tags/headers when parsing because I knew there was a possibility of the format being different. So first, I looped through the first element in the element tree to get the headers used for the .tsv file (issuer, titleOfClass, cusip etc.).

Since the format of the 13F xml can be different, I chose not create a set using a set comprehension which would take one line of code (and looks a lot cleaner):

issuer = {h.text for h in soup.find_all((lambda tag: 'issuer' in tag.name.lower()))}

(notice how we need to know the tag here)

Instead, I looped through the tags and their nested tags (if the tag has children) and added the attributes to a list called data, which includes all relevant data of the xml. Data is then used to write the .tsv file