Reasoning on Time-Series for Financial Technical Analysis

arXiv — cs.LG•Thursday, November 13, 2025 at 5:00:00 AM

The introduction of Verbal Technical Analysis (VTA) marks a significant advancement in financial technical analysis by integrating verbal reasoning with time-series data. Traditional forecasting models primarily rely on textual analysis, often neglecting the rich insights that historical price data can provide. VTA addresses this gap by converting stock price data into textual annotations, allowing for a more nuanced reasoning process. This innovative approach has demonstrated state-of-the-art forecasting accuracy in experiments conducted across major markets, including the U.S., China, and Europe. The ability to produce interpretable forecasts not only enhances the utility of stock predictions for investors but also aligns with the growing demand for transparency in AI-driven financial tools. As the financial landscape continues to evolve, frameworks like VTA could redefine how analysts and investors approach stock forecasting, making it more accessible and understandable.

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