Predicting Stock Market with AI Model

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  https://www.kiplinger.com/

Inspiration: We thought it would be cool if we could predict the stock market

What it does: The AI model can predict closing prices of any stock.

How we built it: Used jupyter notebook for the entire project. It was developed using python. For the back-end we used XGBoost Machine Learning Model to predict the stock prices. For the front-end we used HTML and Python.

Challenges we ran into: Small errors often caused huge issues in the pre-development stage. We prioritized Object Oriented Programming in later stages.

Accomplishments that we're proud of: Even after creating the machine learning model we created a website to integrate it.

What we learned: Didn't expect the model to follow the actual trends. The model was fed high, low, open, close, volume, adj close, and the next days close values for training. However there are many other factors which affect the model so I didn't expect it to work. Since it works, this means that the values I fed to the model also play a massive part in determining the close price.

What's next for Predicting Stock Market with AI Model: The Model doesn't have access to external events which also affect stock prices such as covid. By increasing the amount of data given, It could pick up the sudden change of trend.

Built With

• html
• jupyternotebook
• python