Automate stock trades with AI-driven technical analysis & Alpaca Trading

Paul

1061 views

2/3/2026

Webhook Trigger Data Transformation API Data Enrichment

Official Page

📊 AI-Powered Stock Analysis & Auto-Trading Workflow

Supercharge your trading decisions with this end-to-end AI automation that connects market intelligence, technical analysis, and automated trade execution — all without manual intervention.

My results so far:

(100k paper trading account with the current template strategy)

🚀 What This Workflow Does

Live AI-Driven Market Scanning
Integrates with Danelfin’s AI scoring system to identify top stocks daily based on technical, fundamental, sentiment, and risk scores.
Advanced Technical & Trend Analysis
Combines chart patterns, Fibonacci retracements, Bollinger Bands, MACD, RSI, EMA trends, and support/resistance detection with real-time news sentiment to produce clear, professional-grade analysis reports.
Chart Image AI Analysis
Uses LLM-powered vision models to interpret candlestick charts visually and extract pattern, trend, and indicator insights.
Automated Trade Execution
Integrates with Alpaca Paper Trading API for secure, rule-based buy/sell execution.
Includes:
- Risk management (position sizing, stop-loss/take-profit)
- Account balance & buying power checks
- No-repeat-loss policy
Data Storage & Strategy Memory
Logs trades, PnL, and objectives in PostgreSQL for ongoing strategy refinement.
Automated Reporting
Sends deep-dive market and trade reports directly to your email.

🔗 Integrated Services

Danelfin API – AI-based stock ranking
Supabase Vector Store – Strategy and knowledge retrieval
TwelveData API – Market prices & indicators
Chart-img API – TradingView chart generation
Alphavantage – News sentiment feed
Alpaca API – Automated order execution
OpenAI, Anthropic, Cohere, OpenRouter – Multi-model AI reasoning

📥 Perfect For

Quantitative analysts testing strategies
Investors looking for data-backed, automated execution
Educational environments for learning AI-based market strategies
People that want to know Real results Results

💼 What You Get

Full Setup

Pre-configured n8n workflow with all nodes and logic ready to run
Step-by-step API key integration guide for Danelfin, Alpaca, TwelveData, Alphavantage, Chart-img
Database logging setup with PostgreSQL schema
Automated email reporting template

Detailed Description

Explanation of every sub-agent and AI integration
How the strategy agent selects stocks based on AI scores and past trades
Deep technical indicators breakdown (EMA, RSI, MACD, Fibonacci, Bollinger, Support/Resistance)
Risk management methodology and allocation rules

Examples

Daily Automated Analysis: Every morning the system emails you the top 3 stocks to watch, with price, chart, and sentiment score
Trade Execution: System buys AAPL with a defined stop-loss and take-profit based on technical setup
Chatbot Mode: Ask “What’s the trend on TSLA?” and get a concise, professional-grade market report instantly

💡 Why You’ll Love It

This isn’t just an automation — it’s a full-stack AI trading assistant that thinks, analyzes, and executes while keeping risk in check. From sourcing the idea to placing the trade, it’s all covered.

🔑 Get Started

Replace the placeholder API keys, set your trading preferences, and let the automation do the heavy lifting.

n8n AI-Driven Stock Trading Automation Workflow

This n8n workflow demonstrates a sophisticated setup for automating stock trading decisions using AI-driven technical analysis. It leverages various AI components (Language Models, Embeddings, Vector Stores, and Tools) to process information and potentially generate trading signals or insights.

Description

This workflow acts as a blueprint for an AI agent capable of performing complex tasks related to financial analysis and decision-making. It integrates several Langchain nodes to build an intelligent system that can interact with external tools, process and store information, and potentially communicate findings via email.

What it does

Schedules Execution: The workflow is triggered on a predefined schedule, allowing for regular, automated analysis.
Initial Data Preparation: Sets up initial variables or data points required for the AI agent's operation.
AI Agent Initialization: An AI Agent is configured with specific tools and a language model (Anthropic Chat Model or OpenRouter Chat Model).
Tool Integration:
- Calculator: Provides the AI agent with mathematical computation capabilities.
- Call n8n Workflow Tool: Allows the AI agent to trigger other n8n workflows, enabling complex sub-tasks or external system interactions.
- Think Tool: A specialized tool for the AI agent to perform internal reasoning or planning steps.
- AI Agent Tool: Potentially allows for nesting AI agents or defining specific sub-agents for specialized tasks.
Data Loading and Processing (RAG - Retrieval Augmented Generation):
- Default Data Loader: Loads data, likely from a specified source (though not explicitly defined in this JSON, it's a common use case for this node).
- Recursive Character Text Splitter: Breaks down large texts into smaller, manageable chunks for processing.
- Embeddings OpenAI: Generates vector embeddings for the text chunks using OpenAI's embedding models.
- Supabase Vector Store: Stores and retrieves these vector embeddings, enabling the AI agent to query and retrieve relevant information from a knowledge base.
- Reranker Cohere: Re-ranks retrieved documents to improve relevance before they are fed to the language model.
Language Model Selection: Configures either an Anthropic Chat Model or an OpenRouter Chat Model as the core language model for the AI agent.
OpenAI Integration: Includes a separate OpenAI node, which could be used for direct calls to OpenAI APIs for tasks like text generation, summarization, or other AI functions outside the main agent loop.
HTTP Request: A generic HTTP Request node is included, suggesting the ability to interact with external APIs, potentially for fetching real-time market data, executing trades, or posting results.
Data Transformation: Utilizes Merge, Aggregate, Limit, Split Out, and Markdown nodes for various data manipulation, structuring, and formatting tasks throughout the workflow.
Conditional Logic: A Filter node allows for conditional processing based on specific criteria, enabling dynamic decision-making within the workflow.
Email Notification: A Gmail node is present, indicating the capability to send email notifications, likely for alerts, summaries of trades, or critical analysis results.
Documentation: A Sticky Note node is used for internal documentation within the workflow.

Prerequisites/Requirements

n8n Instance: A running n8n instance (self-hosted or cloud).
AI Credentials:
- OpenAI API Key: For Embeddings OpenAI and OpenAI nodes.
- Anthropic API Key (if using Anthropic Chat Model).
- OpenRouter API Key (if using OpenRouter Chat Model).
- Cohere API Key (for Reranker Cohere).
Supabase Account: For the Supabase Vector Store to store and retrieve vector embeddings.
Gmail Account: For sending email notifications.
External APIs: Any APIs required for the HTTP Request node (e.g., stock market data APIs, trading platform APIs).

Setup/Usage

Import the Workflow: Import the provided JSON into your n8n instance.
Configure Credentials:
- For each AI-related node (OpenAI, Anthropic, OpenRouter, Cohere), configure the respective API keys as credentials in n8n.
- Set up your Supabase credentials for the Supabase Vector Store node.
- Configure your Gmail account credentials for the Gmail node.
Customize Nodes:
- Schedule Trigger: Adjust the schedule as needed for how frequently you want the workflow to run.
- HTTP Request: Configure the URL, headers, and body for any external API calls (e.g., Alpaca Trading API, market data providers).
- AI Agent: Customize the prompt, tools, and language model parameters within the AI Agent node to define its specific trading strategy and analytical capabilities.
- Default Data Loader: Specify the source and method for loading documents into the vector store.
- Filter: Define the conditions for filtering items based on your trading logic.
- Gmail: Customize the recipient, subject, and body of the email notifications.
Activate the Workflow: Once configured, activate the workflow to enable automated execution.

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