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. The efficient-market hypothesis suggests that stock prices reflect all currently available information and any price changes that are not based on newly revealed information thus are inherently unpredictable. Others disagree and those with this viewpoint possess myriad methods and technologies which purportedly allow them to gain future price information. Here we make use of Facebook's Time Series forcasting algorithm Prophet to predict stock market price of US based companies in real teim using multi-variate, single step forecasting strategy.
Download or clone project from github
$ git clone https://github.com/nityansuman/warren.git
Create a project environment (Anaconda recommended)
$ conda create --name envname python
$ conda activate envname
Install prerequisites
$ pip install -r REQUIREMENTS.txt
Run project
$ cd warren
$ python runserver.py
Facebook (Stock: FB) Validation
Microsoft (Stock: MSFT) Validation
Google (Stock: GOOGL) Validation
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Open to all types of collaboration. Feel free to raise a PR.
