https://github.com/adamlouly/stockprediction

Stock prediction using KNN regression, Linear regression and aka LSTM
https://github.com/adamlouly/stockprediction

Last synced: 4 days ago
JSON representation

Stock prediction using KNN regression, Linear regression and aka LSTM

• Host: GitHub
• URL: https://github.com/adamlouly/stockprediction
• Owner: AdamLouly
• License: gpl-3.0
• Created: 2018-12-15T22:35:36.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2018-12-15T22:37:58.000Z (about 6 years ago)
• Last Synced: 2024-12-15T10:47:16.403Z (11 days ago)
• Language: Jupyter Notebook
• Size: 281 KB
• Stars: 1
• Watchers: 1
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Stock Price Prediction Using Multiple Algorithms

##Introduction:

*   Machine learning and deep learning have found their place in the financial institutions for their power in predicting time series data with high degrees of accuracy and the research is still going on to make the models better. This project was done in order to complete the academic project of Data Mining.

##Project workflow

The workflow for this project is essentially in these steps:

*  Problem Understanding

*  Linear Regression

*  KNN

*  LSTM (Deep Learning)

*  Conclusion

1- Problem Understanding

###What are Stocks?

*  Stock represents a claim on the company's assets and earnings. As you acquire more stock, your ownership stake in the company becomes greater.” 

###What is stock price prediction? 

*  Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. 

*  Stock market analysis is divided into two parts:

      1.   Fundamental analysis : involves analyzing a company’s financial statements to determine the fair value of the business 

      2.   Technical analysis : assumes that a security’s price already reflects all publicly-available information and instead focuses on the statistical analysis of price movements.

We will use dataset from Quandl (A website where you can find historical data of stocks) mainly the (TATAGLOBAL) stock.