P1 Select: News-Driven Stock Selection Powered by AI

P1 Select is a quantitative stock selection system purpose-built to evaluate the real-time impact of news events on financial markets. By integrating advanced natural language processing (NLP) methodologies with a structured financial knowledge base, the system converts unstructured news data into actionable investment intelligence. The platform automates the entire analytical workflow—from data ingestion and sentiment extraction to investment-grade recommendation—delivering timely, data-driven support for market-sensitive decision-making.
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In contrast to conventional sentiment analysis tools, P1 Select employs a multi-stage algorithmic architecture capable of capturing the nuanced influence of market-relevant news. It evaluates not only sentiment polarity, but also event criticality, market positioning, and recurrence frequency. This layered analytical approach enables precise classification of news-driven signals, ranging from neutral to high-impact indicators such as “strong bullish” or “strong bearish.”

Technical Overview

Event-Based Sentiment Analysis and Market Impact Evaluation

Continuously monitors global financial news and real-time market updates, applying advanced NLP models fine-tuned for financial semantics.

Interprets complex narratives to extract sentiment cues and quantifies market impact, generating clear investment signals and risk alerts.

Multi-Stage Stock Rating Engine

Employs a proprietary rating algorithm that assesses news influence across multiple vectors, including event severity, headline prominence, and mention frequency.

Dynamically adjusts stock sentiment scores using a tiered classification scheme—Bullish, Bearish, Neutral—with intelligent escalation to Strong Bullish or Strong Bearish based on cumulative signal aggregation.

Intelligent Stock Mapping and Industry Linkage

Automatically identifies equities most likely to be influenced by specific news events through advanced entity recognition and contextual market inference.

Integrates sector-level correlation analysis to uncover indirect exposure pathways, enabling detection of secondary opportunities and systemic risk drivers.