How to Build Stock Researcher AI Agent

For traders and finance professionals, performing research is one of the most cumbersome aspects of the job. 

Sifting through documents, web searches, and internal databases for pertinent information can take hours. And in the fast-changing world of stocks, these delays can lead to erroneous research.

At Stack AI, we’ve seen traders and other finance professionals solve this dilemma by building AI agents that automatically write research reports on stocks in seconds.

After seeing several of these AI agents in action, we want to share how you can build them yourself in the following blog.

LLMs: Improving the Stock Research Process 

Banks, investment firms, and other financial institutions all rely on financial research to make profitable stock trades. 

Historically, this process has involved document analysis (10-K, 10-Q, etc.), web research, scouring in-house databases, and other sources of information. Reports are generated from this information, taking potentially hours to produce.

But with the advent of large language models, the stock research process has changed. Banks and other financial institutions can now use LLMs to analyze many different data sources at once, and automatically produce pre-written reports about stocks detailing the pros and cons of each option. 

However, deploying AI into financial institutions has created its own challenges. Banks and financial institutions must adhere to strict privacy and security standards, protecting PII and account data. 

In recent years, new AI builder tools such as Stack AI have emerged that allow banks to develop their own stock research assistants, while still maintaining the privacy and security standards required of financial institutions. 

In the next section, we’ll share a step-by-step guide on how to build a Stock Research Assistant in Stack AI. 

How to Build an AI Agent for Stock Research

As a first step, sign in to your Stack AI account. In the Stack AI dashboard, select ‘New Project’. Then select the ‘Workflow Builder’. 

In the Templates section, choose the ‘New Project’ option. This will present you with a pre-built workflow for an AI agent. 

Rename the Text Input box to ‘Stock Ticker’. Navigate to the Knowledge Base section, add boxes for Web Search and LinkedIn. 

Connect the boxes to your Stock Ticker text input. Then connect the boxes to the OpenAI LLM.

Now navigate to the OpenAI LLM node. Choose ‘GPT-4o’ from the drop down box. 

Enter the following prompt into the ‘Instructions’ Section:

You are a stock researcher. You will receive a stock and generate a report with the following sections:

Business Overview 

Stock Performance

Recent News 

Market Sentiment 

Respond in elegant markdown and in a well organized text.

Now click on ‘Add Tool’ at the bottom of the LLM. Under ‘Yahoo Finance’, you’ll see two Tools: Stock Ticker Info and Finance Analytics. Add both of them.

Now enter the following text into the Prompt box:

Click on the Export Tab. Give your AI agent a name, description and fill in other details.

Now type in the name of a stock. The AI agent will generate a pre-written report on the stock for you.

Speed Up Your Stock Research, Make More Profitable Trades 

For financial professionals, researching stocks is a time-consuming process, and can lead to missed deals. 

By building this AI agent with Stack AI, finance teams can automate the process of stock research with LLMs. This allows them to perform more profitable trades in shorter amounts of time.  

Want to build your own Stock Researcher? Follow this guide and sign up for a free account with Stack AI to