By the end of this video you will know how to build your own local AI Trading Engine. I built a custom AI trading system from scratch using Claude Opus and VectorBT to develop and backtest strategies locally. This video walks through the entire setup and framework.
I demonstrate how to configure the local trading engine, set up Claude in VS Code, and build system prompts for strategy development. We cover data splitting to prevent bias, running initial backtests, and integrating tools like TA-Lib for indicator testing. The process highlights the performance benefits of local execution over platforms like TradingView.
– Setting up the development environment with Claude Code and VS Code
– Building a VectorBT-based trading engine for efficient backtesting
– Configuring in-sample and out-of-sample data to prevent overfitting
– Running and analyzing initial backtest results for simple indicators
– Comparing local execution speed and hardware considerations with TradingView
LINKS:
Start free as a beta-tester now:
https://www.signalswap.io
Get My Strategies: https://whop.com/tradetactics/
Discord (Find the full price data in the video here): https://discord.gg/dJ6ZCxENEw
All of my social media links: https://linktr.ee/tradingtactics
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YOUTUBE CHAPTERS
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0: 00 Introduction to AI Trading System
0: 46 Trading Engine and Price Data
1: 57 Setting Up Visual Studio Code
3: 10 Navigating Folders and Launching Claude
4: 27 Using Claude with Droid System
6: 09 Building System Prompts
7: 24 VectorBT Trading Engine Overview
8: 27 Building Custom Indicators
9: 25 Hardware and Performance Benefits
11: 23 Data Splitting and Bias Prevention
12: 48 Building Trading Framework
14: 05 Monte Carlo Simulations and Randomization
14: 55 SignalSwap Platform Overview
15: 43 Running Initial System Tests
16: 41 Using TA-Lib for Indicator Testing
17: 52 Automated Environment Setup Process
18: 39 Backtest Speed and Hardware Considerations
19: 27 First Successful Backtest Results
20: 44 Building Complex Strategies with Claude
22: 20 TradingView vs Local Execution
23: 50 Optimizing Drawdown and Sharpe Ratio
24: 52 TradingView Integration and Community Resources
25: 38 Additional Stress Testing Methods
26: 58 Conclusion and Q&A Invitation
#AITrading #AlgorithmicTrading #Backtesting #PythonTrading #QuantitativeFinance
Disclaimer:
The information provided by Trade Tactics and its affiliates is for educational purposes only and is not intended as investment or trading advice. The user bears sole responsibility for any actions taken based on this information and Trade Tactics and its affiliates will not be held liable for any losses or damages resulting from its use.