Stock Price Prediction using Machine Learning

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Description: Stock Price Prediction using Machine Learning Dhruvkumar Patel Contents What is Stock Market? Why to predict Stock Price? Method: LSTM Dataset Results Conclusion What is Stock Market? The Stock Market refers to public markets that exist for

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slide1. Stock Price Prediction using Machine Learning Dhruvkumar Patel<br>
slide2. Contents What is Stock Market?
Why to predict Stock Price?
Method: LSTM
Dataset
Results
Conclusion<br>
slide3. What is Stock Market? The Stock Market refers to public markets that exist for issuing, buying, and selling stocks that trade on a stock exchange or over-the-counter. 
Stocks, also known as equities, represent fractional ownership in a company, and the stock market is a place where investors can buy and sell ownership of such investible assets.<br>
slide4. Why to predict Stock Price? To eliminate the uses of Fundamental Analysis(Long Term).
To eliminate the uses of Technical Analysis(Short Term).
To eliminate the uses of Quantitative Analysis(Historic Data)<br>
slide5. Method: LSTM LSTM stands for Long Short Term Memory.
It is a model that extends the memory of Recurrent Neural Networks (RNN), which is capable of learning long term dependencies.
It is capable of capturing the patterns of both long term such as a yearly pattern and short term such as weekly or daily patterns.<br>
slide6. Why to use LSTM? Using LSTM, time series forecasting models can predict future values based on previous, sequential data and it is proven to be extremely effective. 
The reason they work so well is that LSTM can store past important information and forget the information that is not.
The different gates inside LSTM boost its capability for capturing non-linear relationships for forecasting.<br>
slide7. LSTM Model<br>
slide8. Dataset Apple Last 1 year(3/15/21 to 3/11/22) Apple (1/1/19 to 3/11/22) Train Data: 70% 
Test Data: 30%<br>
slide9. Results Apple Stock of Last 1 Year(3/15/21 to 3/11/22) MAE: 4.11
MSE: 27.17
RMSE: 5.21<br>
slide10. Prediction of Next 5 Days<br>
slide11. Results[Continue] Apple Stock From 1/1/19 to 3/11/22 MAE: 7.34
MSE: 76.74
RMSE: 8.76<br>
slide12. Prediction of Next 30 Days<br>
slide13. Conclusion We don't need the exact stock values of the future, but the stock price movements, i.e. if it is going to rise or fall in the near future.
This LSTM model predict the data in smooth curve.
This LSTM model predict data with MAE,RMSE between 4 to 8 which is efficient to predict accurate price.<br>
slide14. References Prashant Sharma, Machine Learning for Stock Market Prediction
(https://www.analyticsvidhya.com/blog/2021/10/machine-learning-for-stock-market-prediction-with-step-by-step-implementation/?custom=TwBL912)
Stock Price Prediction- Machine Learning
(https://data-flair.training/blogs/stock-price-prediction-machine-learning-project-in-python)
Stock Market Prediction using Machine Learning (https://www.mdpi.com/2079-9292/10/21/2717/pdf)
Avijeet Biswal, An Easy Guide to Stock Price Prediction Using Machine Learning
https://www.sciencedirect.com/science/article/pii/S1877050920307924
https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00333-6<br>
slide15. THANK YOU!<br>