Case study
AI Agent that Automatically Detects Market Moving Events
A detailed description of the case study can be found below
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New Clarity design an AI-powered agent used to monitor real-time news feeds, identify market events likely to trigger stock price movements, estimate the probability of such movements over the next 30 days, and continuously refine its predictive accuracy through feedback-driven machine learning.
In this project, we designed and deployed an AI-driven agent that continuously scans various sources of market news for breaking events related to publicly traded companies, determines which ones are most likely to move stock prices based on a proprietary statistical model, calculates the probability of movement within the next 30 days, and then feeds actual results to the machine learning model to continuously improve accuracy.
It is well known that new information released by public companies can often result in significant price movements in the underlying stock price. However, in a sea of news alerts, press releases, and social media chatter, it’s nearly impossible to know, without wasting hours of human analysis, which events actually matter. The client needed a solution that could cut through the noise, spot price-moving events instantly, and adapt to the changing dynamics of the market.
The team at New Clarity built a fully custom AI agent tailored to the client’s trading strategy that includes event types acquisitions, new contract wins, FDA approvals, forecast changes, stock repurchase announcements, and more. The models also take into consideration the company market cap, trading volume, and other variables to come up with an options trade recommendation.
The AI agent continuously ingests news APIs, SEC filings, analyst reports, and more to capture all potentially interesting events that would fit the criteria for the particular strategy. The natural language processing engine determines if the event is in fact the type of event we are looking for before it even proceeds with the analysis. Without the NLP engine, there would be no way to know for sure if this is an appropriate event to analyze and suggest as a potential trade.
Once an event is detected, our proprietary machine-learning AI model calculates the probability of a price movement within the next 30 days.
Unlike static “set and forget” systems, this AI agent learns from every prediction it makes. After 30 days, the actual price movement, along with all of the critical market data for that stock is fed back to the ML model. The ML parameters are be updated, and the accuracy is continuously improved over time. A
Predictions are delivered through a clear, actionable dashboard. Events are ranked by confidence level, sector, and relevance, allowing teams to instantly spot what matters most and which ones they want to place trades on.
Within the first 30 days, the AI agent was already outperforming markets. The performance measurement system began tracking continuous improvements over time as the system become more intelligent with new training data.
For the client, this meant more timely trades, fewer missed opportunities, and a measurable edge in a highly competitive space.
For financial firms, hedge funds, and research teams, predictive AI agents like this can mean the difference between catching a wave early and missing it entirely. Whether you want to track equities, commodities, or emerging markets, New Clarity AI can build a system to fit your exact needs.
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