Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/souvik-basak/stock_market_prediction
https://github.com/souvik-basak/stock_market_prediction
Last synced: about 20 hours ago
JSON representation
- Host: GitHub
- URL: https://github.com/souvik-basak/stock_market_prediction
- Owner: souvik-basak
- Created: 2022-11-04T15:24:21.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2022-12-01T15:15:26.000Z (about 2 years ago)
- Last Synced: 2024-11-11T04:45:57.603Z (about 2 months ago)
- Language: Python
- Size: 1.66 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# stock_market_prediction
With this project, we are designing an ML algorithm to predict stock market prices and crashes by only relying on past and present information. We collected data from YFINANCE. We will predict whether the market will crash within the timeframe selected by the user (up to six months of timeframe) from now using these data at any point in time. We trained and tested linear regression models, logistic regression models, Support Vector Machines(SVM), decision trees, and Recurrent Neural Network-Long Short Term Memory(RNN-LSTM). A stock market crash is a sharp drop in the total value of a market with prices typically declining more than 10% within a few days. A crash happens due to a massive sell-off that occurs when a majority of market participants try to sell their assets at the same time and is attributable to the burst of a price bubble(price bubbles imply that markets are inefficient)