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A full-stack webapp that allows users to analyze sector performance, their daily stock prices, the risk and return, and how daily prices between competitive stocks correlate with one another in their portfolios.

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davidthinh/Stock-Analysis-Tool

 
 

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Stock Analysis

Deployed on AWS http://54.185.214.209/

Watch Final Screencast (Click on the image below)

Final Project Screencast

Description

Stock Analysis provides an analysis tool which helps users to analyze stocks data more quickly and easily. Users can analyze the daily stock prices,the risk and return and how daily prices between competitive stocks correlate with one another in their porfolios. Below is a summary of all features in the web app.

  • Correlation Analysis
  • Risk and Return Analysis
  • Current Market Information
  • Daily Price
  • Daily Price Variation
  • Sector Performance
  • Ticker lookup
  • Company Information

This web-app is built on a Flask server with Postgres SQL database with SQLAlchmey as the ORM. One year of daily price data for 30 stocks is saved in the database. In the backend, a large of amounts of dataset is analyzed using Python Pandas library. Four different graphs are rendered by using Charts JS. The front end templating uses Jinja2. The HTML is built using Bootstrap. Javascript uses AJAX and JSON to interact with the backend. Database and server routes are tested using the Python unittest module.

Tech Stack

  • Backend: Python, Flask, SQLAlchemy, PostgreSQL, Python unittest module

  • Frontend: Javascript, AJAX, JSON, Bootstrap, Charts.JS, HTML, CSS, JQuery, Jinja2, Flask

  • APIs: Alphadvantage, iexcloud

Installation

  • Clone repository

    $ git clone https://github.com/thuytpham/Stock-Analysis-Tool.git

  • Create database

    $ createdb stocks

  • Create a Virtual Environment

    $ virtualenv env

  • Activate the Virtual Environment

    $ source env/bin/activate

  • Install the dependencies

    $ pip install -r requirements.txt

  • Run the app

    $ python3 server.py

  • Run the test file

    $ python3 testing.py

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A full-stack webapp that allows users to analyze sector performance, their daily stock prices, the risk and return, and how daily prices between competitive stocks correlate with one another in their portfolios.

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  • HTML 58.0%
  • Python 40.9%
  • CSS 1.1%