Asset Analyzer
📌 Type
Independent
Tool Creation
⚜️ Domain
Financial Markets
Investing & Trading
💻 Technologies
Python (Google Colab)
pandas
numpy
matplotlib
seaborn
🕹️ Skills
Data Analysis
Data Visualization
Advanced Python
Economics
📈 Created a Python module 🐍 with classes and functions useful for analyzing assets from Yahoo Finance like stocks, commodities or crypto for trading and investing strategies.
💻 Used pandas, numpy, matplotlib, and seaborn for features like plotting prices, volume, moving averages, normalize values, get date values, get personalized returns, calculate historical volatility, Bollinger bands, compare assets, correlations and more!
🔎 Performed several Analyses on the S&P 500, its sectors, health care, energy, Bitcoin, meme stocks, commodities like oil and gold, and looked for the best stocks. Results are in the "analyses.ipynb" file in GitHub.
⤵️ The use of the module is encouraged for your own projects in Google Colab or other environments by downloading and importing it, a how-to file is available in GitHub. There are several variations, .py and .ipynb files, and with only the classes or only the functions.
💡 The module features detailed documentation, examples, code comments and section structure for developers who might be interested in taking a look. There is also a demonstration file showcasing its capabilities.
Screenshots
Python Code
Written in a Jupyper Notebook of Google Colab, all in one file 'asset_analyzer.ipynb'.
You can get the .ipynb file in GitHub!
Story of the Project
I wanted to create a project that could be a useful tool for others and that was inspired by curiosity and the application of Python as a tool for computation and visualization. So with my advanced Python skills and domain knowledge of financial markets, investing and trading, I created this module and performed analyses with it. 🐍
I learned a lot more about Python and now I am even more comfortable with it to face new challenges. An important note is that I took advantage of ChatGPT 3.5 for code snippets and ideas for the project for a quicker elaboration, but most of it was thought and put together by myself. 🧠