Tesla Financial Market Data Analyst Tool
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Automate sophisticated financial market analysis for Tesla (TSLA) with this AI-powered n8n workflow. Leverage multi-timeframe technical indicators and candlestick patterns to generate actionable trading insights.
About This Workflow
The Tesla Financial Market Data Analyst Tool is a sophisticated n8n workflow designed to provide deep analytical insights into Tesla's stock performance. It harnesses the power of AI agents and specialized tools to process technical indicators and candlestick patterns across multiple timeframes (15-minute, 1-hour, and 1-day). By integrating data from Alpha Vantage and applying advanced analytical logic, this tool identifies trends, potential reversals, and overbought/oversold conditions. The output is a structured JSON report detailing a buy, sell, hold, or cautious signal with a confidence score, making it an invaluable asset for quantitative trading strategies.
Key Features
- Multi-Timeframe Analysis: Evaluates 15m, 1h, and 1d intervals for comprehensive market perspective.
- Advanced Technical Indicators: Utilizes RSI, BBANDS, SMA, EMA, ADX, and MACD for in-depth analysis.
- Candlestick Pattern Recognition: Identifies key price action formations for trading signals.
- AI-Driven Insights: Employs a specialized AI agent to synthesize complex data into clear trading recommendations.
- Structured JSON Output: Delivers actionable insights in a machine-readable format for downstream automation.
How To Use
- Trigger Setup: Configure the 'When Executed by Another Workflow' node to receive
messageandsessionIdinputs. - AI Agent Configuration: In the 'Tesla Financial Market Data Analyst' node, ensure the
textparameter is correctly mapped to the incomingmessage. - Tool Integration: Connect the 'Tesla 15-Minute Indicators Tool', 'Tesla 1-Hour Indicators Tool', and 'Tesla 1-Day Indicators Tool' nodes. Crucially, ensure their respective
workflowIdparameters point to the correct sub-workflows for fetching indicator data. - Input Mapping: Within each tool node, map the
messageandsessionIdto the appropriate input fields, utilizing$fromAIfor dynamic message generation where applicable. - Memory Setup: Configure the 'Simple Memory' node if conversational context is desired for the AI agent.
- Execution: Trigger the main workflow with the necessary inputs to initiate the data fetching and analysis process.
Apps Used
Workflow JSON
{
"id": "94e622f9-fa04-4f45-bb83-61c3369268c2",
"name": "Tesla Financial Market Data Analyst Tool",
"nodes": 18,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 94e622f9-fa04...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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