We were looking through the available API's that were available to us, and we thought that Blackrock's api that gave various data regarding investment portfolios and securities was very interesting. However, when we looked at the get that the api returned the json text file was very difficult to read and interpret, so we decided to find a way to make it easier to interpret that data.
What it does
The script takes the securities data of a particular security, obtained from blackrock's api, and then uses matplotlib to plot the securities return, risk, and sharpe ratio's as a function of time over a given time period.
How we built it
We used the blackrock api, as well as the matplotlib package in order to built our project.
Challenges we ran into
At many major points in our project, we encountered challenged. For instance, we first needed to teach ourselves many new skills like how to use the blackrock api, interpret json files, etc. in order to create our project. Also, finding out in the first place what all the data that blackrock's api spat out.
Accomplishments that we're proud of
Coding this project forced us to learn valuable skills like how to use API's, how to effectively install and use important python packages, as well as many other things that we can walk away with after the hackathon.
What's next for Graphic Financial Risk Data
Given more time and development, all the data spewed out by blackrock's security's data api could be neatly sorted, and then manipulated to try to find various indicators for what might happen to a security in the future. Various methods of technical analysis and signals already exist, and making it easier to read and interpret that data could lower the bar of entry to investing, and allow more people to practice good wealth management.