Implementing the Piotroski F-Score in Python: A Complete Guide for Quantitative Investors

The Piotroski F-Score is one of the most elegant tools in quantitative value investing. Developed by Stanford accounting professor Joseph Piotroski in 2000, it distills a company's financial health into a single number between 0 and 9. In this guide, we'll implement it from scratch in Python. What is the Piotroski F-Score? The F-Score evaluates 9 binary criteria across three dimensions: Profitability (4 points): Is the company making money efficiently? Leverage & Liquidity (3 points): Is the balance sheet improving? Operating Efficiency (2 points): Are margins and turnover improving? A score of 8-9 signals strong fundamentals. A score of 0-2 signals financial weakness. In Piotroski's original study, buying high-scoring stocks and shorting low-scoring ones generated 23% annual returns from 1976-1996. The Implementation def piotroski_f_score ( roa : float , roa_prev : float , ocf : float , total_assets : float , leverage : float , leverage_prev : float , current_ratio : float , current_r