Submission from Team OMR for the TRI-NIT Hackathon
Forecasting stock market prices have always been a challenging task for many business analyst and researchers. Your friend, who is interested in investing in the stock market shares of the well-known company IBM is unable to predict the company's stock market. The rate of his investment and his business opportunities in IBM's Stockmarket can increase if an efficient algorithm could be devised to predict the short term price of an individual stock.
The link below contains a dataset, where the TIME_SERIES_DAILY_ADJUSTED give the stock market's close value of every day with a date. Your task is to devise a model to predict the 'adjusted close' value of the next day given the stocks of all days until the current day, and developer a front-end UI (either Web app or Mobile app) that can help your friend invest the right amount of money
Link to dataset: https://www.alphavantage.co/documentation/
Link to getting an API key: https://www.alphavantage.co/support/#api-key
Our method involves using a Recurrent Neural Network(RNN), in particular it uses LSTMs(Long Short Term Memory).
- Python
- StreamLit
- Kaustubh Khedkar
- Harish Gumnur
- Poorna Hegde
https://drive.google.com/file/d/1w9NFng4gDwuaoE_bE599vF44V8ena1k9/view?usp=sharing