Niraj-kumbhar/Stock_Forcast_project

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.

Stock-Forecast-Dash

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

Screenshots

Getting Started

• 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

Download

  git clone https://github.com/Niraj-kumbhar/Stock_Forcast_project.git

Requirements

• 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

Documentation

• Dash-Plotly - Framework for interactive web applications
• yfinance - offers a threaded and Pythonic way to download market data from Yahoo!Ⓡ finance.

Contributors

Manisha Ahlawat

Disclaimer

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.