• Stars
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    371
  • Rank 115,103 (Top 3 %)
  • Language
    Jupyter Notebook
  • License
    MIT License
  • Created over 8 years ago
  • Updated over 1 year ago

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Repository Details

Regression, Scrapers, and Visualization

Stock Analysis

This repository contains python scripts that I am devleoping to perform analysis on stock prices and visualization of stock prices and other data such as volume.

Some of the goals I want to achieve with this project include:

  • Get the data I need from Yahoo Finance or other API. Able to specify what I need and the time range.
  • Different regression implementations on the close price data. (Linear, SVM, etc.) Possibly try to fit a polynomial function which follows the data.
  • Predicting Stock price for the next day.

Trends

TrendLine.py Results

trendy

trendy

trendy

trendy

Regression

Using my code for linear regression and Nvidia's (NVDA) stock prices of each day. I got a slope of 0.1850399032986727 and a y intercept of 24.54867003005582. The 50.08 number is the price predicted for the next day based on the linear formula it calculated.

[0.1850399032986727, 24.54867003005582]
50.0841766853

Screenshots

Linear Regression performed on NVDA Stock data from January 2016

New Screenshots

AEIS

AEIS February 20

FB

Facebook February 20

Version

1.0.0 - Released Stock Scraper

1.0.1 - Minor bug fixes with duplicate entries in the CSV File

Todo

  • Use Machine Learning algorithms to predict stock close price for the next day
  • Add data visualization with technical indicators such as moving average, volume, STOCH.
  • Add Stock screener, to screen through every stock and see which ones are best buys.

Star History

Star History Chart

License

MIT

Free Software, Hell Yeah!