QuantDinger v3.0.1: better AI strategy building, clearer tuning, and smoother backtesting
We’ve just shipped QuantDinger v3.0.1.
This release is all about making the product more useful in real trading workflows, from AI research and Python strategy generation to backtesting, tuning, and live execution.
New in v3.0.1
Smarter AI-generated strategy and indicator workflow
Better AI quality-check summaries and auto-fix feedback
Clearer AI tuning visibility, so users can see which parameters changed and what was applied
Improved strategy development documentation and synchronized example scripts
Better support for # @param, # @strategy, and tradeDirection
Backtesting fixes and smoother validation flow
Improved multilingual support across key strategy and indicator experiences
Admin and operations improvements, including user export support
Why we made this release
QuantDinger is designed to be more than an AI trading demo. We want it to be a practical self-hosted AI trading operating system for traders, quants, and teams who need:
AI market research
Python-native strategy building
backtesting and parameter tuning
live trading workflows
full ownership of infrastructure and data
v3.0.1 makes that experience more transparent, more stable, and easier to use.
Try it here:
Live demo: https://ai.quantdinger.com
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