by Jean-Louis Hua
How I Use Python
Over the past months, I’ve been learning the basics of Python through Harvard’s CS50: Introduction to Programming with Python.
I now have a solid understanding of the fundamentals (variables, loops, functions, data structures) and I use LLMs to help me write scripts.
My goal isn’t to become a developer, but to use Python as a tool for research and automation: to speed up repetitive tasks, extract financial data, or create simple quantitative screens. Having a basic understanding of the language allows me to read, adapt, and extend the code whenever necessary.
Below are a few simple examples of scripts I created and use in my work, mostly small tools built to support my fundamental investment research.
Industry Data Scraper
I built a script to automatically scrape monthly registration data for motorhomes and caravans from UNI VDL, the French leisure vehicle industry association.
The challenge: the association deliberately changes PDF file names and URL structures each month to prevent automated downloads: sometimes "Statistique-2024-08", sometimes "Stat-juin-2025", and so on.
The script scrapes the UNI VDL statistics page to discover all available PDF links, downloads them automatically, and extracts specific data points from structured tables within each PDF. It then compiles the data into a clean Excel file with historical time series.
This demonstrates practical web scraping skills and automated data extraction from non-standardized sources, useful for gathering industry data that isn't readily available in structured formats.
Drawdown and Beta screener
One of my approaches is to invest in high-quality companies – businesses with strong profitability, durable competitive advantages, and solid long-term fundamentals – that are temporarily penalised by short-term factors such as cyclical downturns or market sentiment.
This tool automatically downloads market prices and betas for hundreds of companies and helps identify those whose share price has fallen by more than 30% from their 12-month high, adjusted for their beta.
It’s a quantitative screening tool designed to save time and broaden the research universe.
It often highlights companies I don’t actively follow but that may deserve a closer look. Once identified, I perform a more qualitative, fundamental analysis – focusing on financial strength, cash generation, competitive position, and management quality – to determine whether the price decline reflects a structural issue or a temporary dislocation.
The tool doesn’t produce investment decisions; it helps prioritise research and structure idea generation within a broad investment universe.
Company Profile Grabber
When screening a large number of companies, I often need a quick way to recall what each business actually does before diving into the financials.
This small script automatically retrieves key information from Yahoo Finance – company name, sector, industry, and a short business description – for a list of tickers stored in an Excel file.
It provides a concise overview of each company’s activity and positioning, making it easier to prioritise which names deserve deeper analysis.
The goal is simply to speed up the first stage of qualitative research and avoid wasting time on businesses outside my investment universe.