Welcome back to the Python for Finance series! In our previous posts, we’ve fetched specific metrics like P/E (Post 1), retrieved full financial statements (Post 2), and visualized profitability trends (Post 3). Now, we shift our focus from profitability to another critical aspect of fundamental analysis: Liquidity. Liquidity refers to a company’s ability to meet its short-term financial…
Welcome back to our Python for Finance series! In the previous post (Post 2), we successfully automated the retrieval of the three core financial statements – the Income Statement, Balance Sheet, and Cash Flow Statement – using Python and the Financial Modeling Prep (FMP) API. We saw how pandas helps structure this data effectively. But raw financial statements, while informative,…
Welcome back to the Python for Finance series! In our first post, we calculated the P/E ratio, seeing how Python could automate fetching specific data points. However, as insightful as ratios like P/E are, they are derived from the company’s core financial reports. To truly understand why a P/E ratio is high or low, or to assess a company’s overall…
Welcome to the inaugural post of our exciting series: Python for Finance! In this series, we’ll explore the powerful intersection of Python programming and financial analysis, specifically focusing on Fundamental Analysis. If you’ve ever wondered about the real value behind a stock price, beyond the daily market noise, then fundamental analysis is your toolkit. It’s the practice of evaluating…
In our journey through building Python stock screeners, we’ve looked at value, dividends, and pure growth strategies individually. But what if you want the best of both worlds? This post dives into multi-factor stock screening with Python, demonstrating how to combine criteria – specifically creating a Growth at a Reasonable Price (GARP) screener and adding a basic technical trend filter. Why Combine…
Welcome back to our Python for Finance series! Having explored value stocks and dividend payers, we now turn our attention to another exciting category: growth stocks. This post will show you how to build a Python growth stock screener to identify companies exhibiting strong expansion potential using yfinance and pandas. What is a Growth Stock? Growth investing focuses on companies expected to grow their…
Welcome Back! In our first post, we laid the groundwork by building a Python screener to identify potential value stocks. Now, we’ll expand our toolkit by focusing on a different, yet equally popular strategy: dividend investing. This guide will walk you through creating a Python script to find stocks offering attractive dividend yields potentially backed by sustainable payout…
In the world of finance, understanding asset performance is key. Investors constantly weigh the potential rewards of high-growth, volatile assets like cryptocurrencies against the stability and historical performance of traditional markets represented by indices like the S&P 500. In this post, we’ll dive into a practical analysis using Python to compare the annual returns of Bitcoin (BTC)…
If you’re looking to merge your Python skills with the world of investing, you’ve landed in the right place. This is the first post in our series dedicated to building practical financial stock screeners using Python. Stock screeners are invaluable tools; they allow us to sift through thousands of companies methodically, applying specific criteria to…
The current investment landscape presents a unique and challenging puzzle for investors. We’re navigating a period marked by significant equity market downturns, heightened market volatility 2025, and persistent economic uncertainty often amplified by geopolitical tensions. However, what makes this moment particularly complex is the unusual weakness observed in assets traditionally considered pillars of stability: the…