How an AI agent can convert post-earnings price and volume movement into a cautious briefing with context and follow-up questions
This workflow gives an AI agent a defined job, a bounded set of records, and a result a person can review. The agent reads the relevant Alpha Vantage context, applies the rules in the prompt, and keeps the source behind every recommendation. It returns a proposed handoff rather than taking consequential actions on its own.
Can an AI agent convert post-earnings price and volume movement into a cautious briefing with context and follow-up questions?
Yes. Start with the scope, date range, decision rules, and fields that identify the right records. The agent can collect the evidence, compare states or sources, mark conflicts and missing data, and organize the result around the outcome above. A reviewer then checks the matches and judgment calls before approving messages, record updates, bookings, purchases, publishing, or other write actions. The guide below shows the records, boundaries, prompt, and handoff needed for this specific workflow.
What this agent helps you do
An Alpha Vantage earnings move briefing agent helps teams understand how selected symbols behaved around an earnings event. It is not a trading bot. Its job is to gather observable market data, highlight unusual movement, and prepare questions for analyst review.
When to use this workflow
Use it the morning after earnings, before an investment committee meeting, or when a watchlist symbol moves sharply and stakeholders need a concise explanation of what changed.
How Alpha Vantage gives the agent context
Connect the plugin and provide symbols, event dates, and comparison windows. Ask the agent to look at available price and volume data, compare movement before and after the event, and clearly separate observed facts from interpretation.
Example starter prompt
Prepare a post-earnings move brief for these symbols. Summarize price and volume behavior around the event, compare it with the previous week, and list follow-up research questions. Do not provide personalized investment advice.Suggested workflow steps
Define the event window, gather market data, calculate or summarize notable movement, compare symbols, and identify outliers. The agent should explain data limitations and avoid claiming causality unless another verified source supports it.
Questions this workflow answers
What changed in a stock after earnings, and which parts of the move need more research?
An agent can prepare a factual event-window brief from price and volume data without pretending the market series explains itself. Give it the symbol, earnings timestamp, exchange timezone, comparison window, and benchmark you want to use. It can show the close before the event, the next available open and close, intraday range when available, volume relative to a chosen baseline, and how the move compares with the previous week or relevant index.
The time boundary matters. Results released after the close should be matched with the next trading session, while a pre-market release may affect that day’s open. Holidays, splits, thin trading, and missing intervals can distort a quick percentage comparison. The agent records the timestamps and adjustments it used and labels any incomplete series. It should also distinguish a gap at the open from movement during the session, since those patterns create different follow-up questions.
Observed data and interpretation belong in separate columns. “Volume was 2.3 times the twenty-day median” is an observation. “Investors disliked guidance” requires a source beyond the price series. The agent can ask whether revenue, margin, outlook, a conference call, or a broader sector move supplied context, but it cannot present one as the cause until the team checks reliable coverage or filings.
The analyst receives a compact table, a timeline, unusual observations, and the next evidence to collect. That might include the release, call transcript, guidance history, peer movement, or company-specific news. The workflow does not recommend buying or selling and should not be used as personalized advice. It gives a reviewer a consistent starting point while the event is fresh and preserves the exact market data behind each question.
Expected handoff
The handoff should include a symbol table, notable moves, risk questions, and suggested next research. A human analyst can use it as a starting point for a deeper memo.