Cyclicity Analysis of Financial Time-Series Data

This repository contains a working implementation of Cyclicity Analysis, which is a pattern recognition technique for analyzing leader follower relationships amongst multiple time-series. We run Cyclicity Analysis on financial time-series pertaining to the stock and cryptocurrency markets.

Downloading Requirements

• Download PyCharm (free edition) from https://www.jetbrains.com/pycharm/.
• Download Python 3.10 from https://www.python.org/downloads/.

Importing Project

• Open PyCharm and select Get from VCS.
• Enter this project's .git link.
• Specify the download location to be the location of your PyCharmProjects folder.
• Download the project.

Installing Project Dependencies Automatically

• You may be prompted by PyCharm to install a Virtual Environment based on the requirements.txt file.
• Follow the onscreen instructions to do so.
• Make sure you specify your installed Python 3 for creating the Virtual Environment.

Installing Project Dependencies Manually

• Open PyCharm Settings and locate the Project: StockMarketAnalysis pane.
• Click on Project Interpreter.
• Add a new VirtualEnv environment with your system Python.
• Restart PyCharm and open its local Terminal, which is located on the bottom of the PyCharm window.
• Type the command pip3 install -r requirements.txt in Terminal to install project dependencies.

API Key

• In order to fetch time-series data, you need to get your own API key from https://polygon.io/.
• For easy data fetching, it is strongly recommended you purchase the Starter plans in https://polygon.io/stocks#stocks-product-cards and https://polygon.io/crypto.
• Inside of the FetchPrices.py, replace the string 'xxxx' with your own API key string.

Jupyter Server Instructions

• Open the local Terminal on PyCharm.
• Type the command jupyter notebook to open up a new Jupyter Server.
• Click on the CyclicityAnalysisDemo.ipynb file to open the notebook.
• Run each code cell using the toolbar on top of the window.