StockOverflow

Inspiration

As the recent pandemic and problems engulfed our society in the past year, stock prices and the market have been filled with chaos and unpredictability. The members of our teams are actively attempting to invest in company stocks, but the recent blows have kept us down. Throughout the course of a year at least 80% of investors in the stock market have lost money. With this in mind, we decided to dedicate this project to that idea and try to improve upon it. Traditional computers only take us so far as to computational speeds, so recently computer scientists have invested time and energy into Quantum Computing, a much more elegant solution to our problems.

What it does

As an aid towards the prompt of modern problems, our program, StockOverflow, is a stock projecting algorithm that incorporates quantum computing into classical mechanics. Our project combines the famililarities of modern computations with the added benefits of quantum mechanics to provide a higher quality of outputs and results. In standard computers, trends are projected by linear regressions, but unlike a simple line we’ve drawn out in math class, a stock trend can be much more complicated and better modeled with an exponential or logarithmic regression of a quantum computer, as we have done in this project.

How we built it

HTML Flask Anaconda Jupyter Notebook IBM Qiskit Python Pandas SKLearn Tensorflow

Challenges we ran into

As most of us are rather rudimentary to computer science and quantum mechanics, this project was difficult for us to pull off. To create the code capable of projecting the stock trends, we spent numerous hours scratching our heads to come up with a successful idea, and eventually succeeded. Also to that point, one of our teammates recently got contaminated with Covid-19 right before the competition started and was forced to stay at home to work instead of meeting together and helping to accomplish the project.