Project guide and refernce credit: Crio.do
Stock Price Forecast App is based on Machine Learning. By providing number of days , we can predict trend in Stock Price. The frontend of App is based on Dash-plotly framework. Model is predicting stock price using Support Vector Regression algorithm. App can predict next 5-10 days trend using past 60 days data.
check this App on heroku: stock-predict-dash.herokuapp.com
- Enter Stock_ticker Eg. AAPL is for Apple. hit
Submit
button. - You can Specify Time range, default is 1st Jan 2020 till today.
- Click on
Stock Price
button to see stock's actual price trend - Click
Indicators
button to see EMA20 Indicator on Stock price trend graph - Enter number between 1-15 and hit
Forecast
button, it will take some time to load predicted future trend
git clone https://github.com/Niraj-kumbhar/Stock_Forcast_project.git
- python3.x
- dash
- Flask
- lxml
- numpy
- pandas
- plotly
- scikit-learn
- gunicorn
- scipy
- sklearn
- yfinance
Install libraries from requirements.txt file
pip install -r requirements.txt
- Dash-Plotly - Framework for interactive web applications
- yfinance - offers a threaded and Pythonic way to download market data from Yahoo!Ⓡ finance.
This software is for educational purposes only. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS. Do not risk money which you are afraid to lose. There might be bugs in the code - this software DOES NOT come with ANY warranty.