Hundreds of thousands of people around the world have lost every single dollar they have to their name by one small mistake: investing in something they really shouldn't. These people aren't able to come back and live their lives again. Luckily, there's now a solution. Introducing Investi Bud, a new Python application that makes reliable investing as easy as clicking a few buttons.
As mentioned previously, it's built on Python, and to obtain the advice for the project, we've used machine learning. The premise is that we've fed it some training information about the S&P, the Dow, and NASDAQ indexes, and from there, it predicted what the future of those stocks would look like using different models. To run the program, the user records a few factors for the program to follow, specifically volatility, the length of the investment, and a budget to match. From there, we input all of this information into our machine learning and it spits out the stocks and bonds that fall under these parameters.
We wanted to do this project because we're interested in investing but when we started trying to understand it, we realized that it was easier said than done. As a result, we wanted to make smart investments more accessible to amateur investors, and this software makes this all come true.
We're proud that we got this idea to end up working and having it look clean, which seemed difficult in the beginning, especially since we're using Python, and the effort that we put in reflected what we got out, which was just as we saw it in our heads. Even with the achievements, throughout the road, there were many obstacles, like the program constantly not operating, until we finally removed all of the bugs and were able to run it. On top of that, making a GUI for the app itself was incredibly difficult and took most of our time.
Even with all of these problems, we've learned a lot, both macroscopically and microscopically. The ideas of Python and using Tkinter weren't simple by any means, and more often than not, the windows for our app simply didn't work during development. Overall, we learned that Python is just really difficult to learn and maneuver within 24 hours.
From this, we'd love to develop the application by making it more user-friendly and having more factors from the user to make the results more accurate. Also, we'd love to have more options related to investing, like predicting how well a stock might do today or a community where users recommend other users to buy certain stocks.
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