Finding Alphas by Igor Tulchinsky explores the multifaceted process of developing quantitative trading strategies, known as alphas. The text examines various data sources, including financial fundamentals, market prices, news sentiment, and even social media, as potential inputs for predictive models. It details methodologies for constructing and backtesting these alphas, emphasizing the crucial aspects of avoiding overfitting and managing risk. Furthermore, the book introduces WebSim™, a platform designed to facilitate alpha creation and evaluation through both code-based and expression-based approaches. Ultimately, the work serves as a guide for researchers seeking to identify and implement profitable trading rules in the complex world of financial markets.