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.
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
This is insanely accurate. I decided to compare this result with result's I would get with a widely known API, famous for machine learning and other regression tools in python. The API is called sci-kit-learn.
Using the linear regression offered from the API We get almost the same result, except with less accuracy.
My method outputs a number with greater significant figures.
Using my regression model:
Using Sci-kit-learn API:
This barely makes a difference to the naked eye. The two graphs are very similar.
1.0.0 - Released Stock Scraper
1.0.1 - Minor bug fixes with duplicate entries in the CSV File
- 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.
- Display technical analysis based on stock prices.
- Add Ratio Analysis & compare ratio with competitors' ratios. (Allow users to define competitors' ratios)
- Add Stock screener, to screen through every stock and see which ones are best buys.
Free Software, Hell Yeah!