Auto Time Series Stock Analysis

Overview

Auto Time Series Stock Analysis is a Python-based project designed to fetch, process, and visualize stock data. It allows users to analyze historical stock prices and related metrics, perform statistical tests, and even predict future prices using deep learning models (LSTM and GRU). The project leverages data from Yahoo Finance and provides interactive visualizations with Plotly.

Features

• Data Acquisition & Preprocessing:
  Fetch stock data using yfinance and clean/prepare data with pandas.

• Visualization:
  Generate interactive charts such as price plots, moving averages, volatility trends, seasonal decomposition, and dividend yield plots using Plotly.

• Statistical Analysis:
  Perform tests like the Dickey-Fuller test to assess stationarity of the time series.

• Deep Learning Predictions:
  Utilize LSTM and GRU models to forecast future stock prices.

Installation

Prerequisites

• Python 3.7 or higher
• pip (Python package installer)

Setup

1. Clone the Repository:

   git clone https://github.com/rrawatt/auto-time-series-analysis.git
   cd auto-time-series-analysis
   

2. Install Dependencies::

   pip install -r requirements.txt
   

3. Test Use:

   python main.py AAPL 2020-01-01 2022-01-01
   

Collab Environment

• Can also run directly as in collab environment with report generation and plots.zip file generation