How to build a Financial Research Agent with SEC Filings and Market Data
Day 5 of 30 Days of Search. Quick Summary: You read the company’s filings, check the share price, and work through the numbers in a spreadsheet. Then you try to make sense of it all: is the business doing well, is the price justified, and what could change that? An agent needs those sources too. A general web summary can give it context, but the revenue number, the risk disclosure, and the price…
Building a financial research agent involves leveraging SEC filings, market data, and economic indicators to generate comprehensive research reports. By integrating Valyu's AI SDK with a TypeScript agent, you can build a system that pulls evidence directly from reliable sources. The process begins with adding the necessary financial search tools using the Valyu SDK and the Vercel AI SDK.
These tools include secSearch for SEC filings and insider transactions, financeSearch for prices, earnings, and financial statements, and economicsSearch for macroeconomic indicators. The agent uses the generateText function to combine these tools and generate a research report. The model can choose which tools to use based on the research question, and the stepCountIs function limits the number of generation steps to control the output.
To add more financial data sources, you can utilize the includedSources parameter in the financeSearch function and choose from various source families such as filings, equity, funds, valuation, and macro indicators. This approach ensures that the agent has access to relevant and structured financial data to support informed decision-making.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
