Stock Price Prediction

An experiment into using machine and deep learning on data related to the stock market

General Outline:

1. Import
2. Data Gathering
3. Data Visualization And Subplots
4. Data Preprocessing
5. Modeling
6. Calculation of Root Mean Squared Error (RMSE)
7. Visualization of Prediction vs Actual
8. Conclusion

Import

Data Gathering

Data Visualization

Subplots

Data Preprocessing

Modeling

Calculation of Root Mean Squared Error (RMSE)

Visualization of Prediction vs Actual

Conclusion

Given the Root Mean Squared Error, the model is able to predict the Closing price for a certain ticker with some error. This can also be visually observed by the Original vs Prediction visualization.

That being said, the prediction is based on historical price movement which isn't the only factor that affects stock prices.

In order to capture price movements better, a combination of factoring other points of data and finetuning the model is needed.

WARNING: Do not invest in the stock market based on this model. The purpose of this project is to inquire into the possibility of using machine learning methods to aid investment.

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