Financial Analysis

TL;DR for operators An analyst must combine financial ratios, management commentary, risk reports, limited research time, and an auditable recommendation. Large language models can summarize those materials fluently, but the harder question is whether prompting alone can make them apply evidence weights and decision rules consistently. CRISTAL separates the work. An LLM converts qualitative reports into structured indicators, while explicit probabilistic code records how each indicator changes the probability of each company category, updates those probabilities, prioritizes additional evidence, and produces the final classification. ...

TL;DR for operators A paper on a “real-time stock analyst” sounds, at first blush, like another attempt to place a crystal ball inside a chatbot and call it alpha. Fortunately, this one is more useful than that. Taniv Ashraf’s paper, A Serverless Architecture for Real-Time Stock Analysis using Large Language Models, is best read as a build-and-debug case study, not as evidence that Gemini can reliably predict stock prices.1 ...