QuantDinger

Next-Gen AI Quantitative Trading Platform

🤖 AI-Native · 🐍 Visual Python · 🌍 Multi-Market · 🔒 Privacy-First

Build, Backtest, and Trade with an AI Co-Pilot. Better than PineScript, Smarter than SaaS.

Official Community · Live Demo · 📺 Video Demo · 🌟 Join Us

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📖 Introduction

What is QuantDinger?

QuantDinger is a local-first, privacy-first, self-hosted quantitative trading infrastructure. It runs on your own machine/server, providing multi-user accounts backed by PostgreSQL while keeping full control of your strategies, trading data, and API keys.

Why Local-First?

Unlike SaaS platforms that lock your data and strategies in the cloud, QuantDinger runs locally. Your strategies, trading logs, API keys, and analysis results stay on your machine. No vendor lock-in, no data exfiltration.

Who is this for?

QuantDinger is built for traders, researchers, and engineers who:

• Value data sovereignty and privacy
• Want transparent, auditable trading infrastructure
• Prefer engineering over marketing
• Need a complete workflow: data, analysis, backtesting, and execution

Core Value

• 🔓 Apache 2.0 Open Source (Code): Permissive and commercial-friendly
• 🐍 Python-Native & Visual: Write indicators in Python with AI assistance, visualize on built-in K-line charts
• 🤖 AI-Loop Optimization: AI analyzes backtest results to suggest parameter tuning, forming a closed optimization loop
• 🌍 Universal Market Access: Crypto (Live), US Stocks (IBKR), Forex (MT5), Futures (Data/Notify)
• 💳 Built-in Monetization: Membership subscription, credit system, USDT on-chain payment
• ⚡ Docker & Clean Arch: 4-line command deployment with modern tech stack

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📺 Video Demo

Click the video above to watch the QuantDinger project introduction

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📚 Documentation

Guides

• Python Strategy Development Guide
• Interactive Brokers (IBKR) Trading Guide 🆕
• MetaTrader 5 (MT5) Trading Guide 🆕

Notification Configuration

• Telegram Notification Setup
• Email (SMTP) Notification Setup
• SMS (Twilio) Notification Setup

📸 Visual Tour

🗺️ System Architecture Overview

A comprehensive view of QuantDinger's AI-powered research, backtesting, and automated trading capabilities.

📊 Professional Quant Dashboard

Real-time monitoring of market dynamics, assets, and strategy status.

🤖 AI Deep Research Multi-agent collaboration for market sentiment & technical analysis.	💬 Smart Trading Assistant Natural language interface for instant market insights.
📈 Interactive Indicator Analysis Rich library of technical indicators with drag-and-drop analysis.	🐍 Python Strategy Gen Built-in editor with AI-assisted strategy coding.
📊 Portfolio Monitor Track positions, set alerts, and receive AI-powered analysis via Email/Telegram.

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✨ Key Features

1. Visual Python Strategy Workbench

Better than PineScript, Smarter than SaaS.

• Python Native: Write indicators and strategies in Python. Leverage the entire Python ecosystem (Pandas, Numpy, TA-Lib) instead of proprietary languages like PineScript.
• "Mini-TradingView" Experience: Run your Python indicators directly on the built-in K-line charts. Visually debug buy/sell signals on historical data.
• AI-Assisted Coding: Let the built-in AI write the complex logic for you. From idea to code in seconds.

2. Complete Trading Lifecycle

From Indicator to Execution, Seamlessly.

1. Indicator: Define your market entry/exit signals.
2. Strategy Config: Simplified creation with smart defaults (15min K-line, 5x leverage, market order). Advanced mode available for full customization.
3. Backtest & AI Optimization: Run backtests, view rich performance metrics, and let AI analyze the result to suggest improvements.
4. Execution Mode:
   • Live Trading:
     • Cryptocurrency: Direct API execution for 10+ exchanges (Binance, OKX, Bitget, Bybit, etc.)
     • US Stocks: Via Interactive Brokers (IBKR)
     • Forex: Via MetaTrader 5 (MT5)
   • Signal Notification: Send signals via Telegram, Discord, Email, SMS, or Webhook.
5. Risk Control: Mandatory disclaimer acknowledgment before live trading. Market order mode by default for reliable execution.

3. AI-Powered Analysis & Trading Radar

Fast, Accurate, Multi-Market Intelligence.

• Fast Analysis Mode: Single LLM call architecture for quick, accurate analysis
• AI Trading Opportunities Radar 🆕: Auto-scans Crypto, US Stocks, and Forex markets every hour, displaying opportunities in a rolling carousel
• ATR-Based Trading Levels: Stop-loss and take-profit recommendations based on technical analysis
• Analysis Memory: Store analysis results for history review and continuous learning
• Strategic Integration: AI analysis can serve as a "Market Filter" for your strategies

4. Membership & Billing System 🆕

Built-in Monetization for SaaS Deployment.

• Subscription Plans: Monthly / Yearly / Lifetime tiers with configurable pricing
• Credit System: Each plan includes credits; lifetime members receive monthly credit bonuses
• USDT On-Chain Payment 💰: TRC20 scan-to-pay with HD Wallet (xpub) address derivation per order, automatic on-chain reconciliation via TronGrid API
• Admin Configuration: All plan prices, credits, and payment settings configurable via System Settings

5. Indicator Community & VIP System

Share, Discover, and Trade Indicators.

• Publish & Share: Share your Python indicators with the community
• Credit-Based Purchase: Buy premium indicators from other users with credits
• VIP Free Indicators 🆕: Mark indicators as "VIP Free" — VIP members can use them without spending credits
• Rating & Reviews: Rate and review purchased indicators
• Live Performance Tracking: Real-time performance stats aggregated from backtests and live trades

6. Universal Data Engine

QuantDinger provides a unified data interface across multiple markets:

• Cryptocurrency: Direct API connections for trading (10+ exchanges) and CCXT integration for market data (100+ sources)
• Stocks: Yahoo Finance, Finnhub, Tiingo (US stocks)
• Futures/Forex: OANDA and major futures data sources
• Proxy Support: Built-in proxy configuration for restricted network environments

7. Memory-Augmented Agents (Local RAG + Reflection Loop)

QuantDinger's agents don't start from scratch every time. The backend includes a local memory store and an optional reflection/verification loop:

• What it is: RAG-style experience retrieval injected into agent prompts (NOT model fine-tuning).
• Where it lives: PostgreSQL database (shared with main data) or local files under backend_api_python/data/memory/ (privacy-first).

flowchart TB
    %% ===== 🌐 Entry Layer =====
    subgraph Entry["🌐 API Entry"]
        A["📡 POST /api/analysis/multi"]
        A2["🔄 POST /api/analysis/reflect"]
    end

    %% ===== ⚙️ Service Layer =====
    subgraph Service["⚙️ Service Orchestration"]
        B[AnalysisService]
        C[AgentCoordinator]
        D["📊 Build Context<br/>price · kline · news · indicators"]
    end

    %% ===== 🤖 Multi-Agent Workflow =====
    subgraph Agents["🤖 Multi-Agent Workflow"]

        subgraph P1["📈 Phase 1 · Analysis (Parallel)"]
            E1["🔍 MarketAnalyst<br/><i>Technical</i>"]
            E2["📑 FundamentalAnalyst<br/><i>Fundamentals</i>"]
            E3["📰 NewsAnalyst<br/><i>News & Events</i>"]
            E4["💭 SentimentAnalyst<br/><i>Market Mood</i>"]
            E5["⚠️ RiskAnalyst<br/><i>Risk Assessment</i>"]
        end

        subgraph P2["🎯 Phase 2 · Debate (Parallel)"]
            F1["🐂 BullResearcher<br/><i>Bullish Case</i>"]
            F2["🐻 BearResearcher<br/><i>Bearish Case</i>"]
        end

        subgraph P3["💹 Phase 3 · Decision"]
            G["🎰 TraderAgent<br/><i>Final Verdict → BUY / SELL / HOLD</i>"]
        end

    end

    %% ===== 🧠 Memory Layer =====
    subgraph Memory["🧠 PostgreSQL Memory Store"]
        M1[("market_analyst")]
        M2[("fundamental")]
        M3[("news_analyst")]
        M4[("sentiment")]
        M5[("risk_analyst")]
        M6[("bull_researcher")]
        M7[("bear_researcher")]
        M8[("trader_agent")]
    end

    %% ===== 🔄 Reflection Loop =====
    subgraph Reflect["🔄 Reflection Loop (Optional)"]
        R[ReflectionService]
        RR[("reflection_records.db")]
        W["⏰ ReflectionWorker"]
    end

    %% ===== Main Flow =====
    A --> B --> C --> D
    D --> P1 --> P2 --> P3

    %% ===== Memory Read/Write =====
    E1 <-.-> M1
    E2 <-.-> M2
    E3 <-.-> M3
    E4 <-.-> M4
    E5 <-.-> M5
    F1 <-.-> M6
    F2 <-.-> M7
    G <-.-> M8

    %% ===== Reflection Flow =====
    C --> R --> RR
    W --> RR
    W -.->|"verify + learn"| M8
    A2 -.->|"manual review"| M8

8. Multi-LLM Provider Support

Provider	Features
OpenRouter	Multi-model gateway (default), 100+ models
OpenAI	GPT-4o, GPT-4o-mini
Google Gemini	Gemini 1.5 Flash/Pro
DeepSeek	DeepSeek Chat (cost-effective)
xAI Grok	Grok Beta

Simply configure your preferred provider's API key in .env. The system auto-detects available providers.

9. User Management & Security

• Multi-User Support: PostgreSQL-backed user accounts with role-based permissions
• OAuth Login: Google and GitHub OAuth integration
• Email Verification: Registration and password reset via email codes
• Security Features: Cloudflare Turnstile captcha, IP/account rate limiting
• Demo Mode: Read-only mode for public demonstrations

10. Strategy Runtime

• Thread-Based Executor: Independent thread pool for strategy execution
• Auto-Restore: Resumes running strategies after system restarts
• Market Order Default: Prioritizes execution reliability over price optimization
• Order Queue: Background worker for order execution

11. Tech Stack

• Backend: Python (Flask) + PostgreSQL + Redis (optional)
• Frontend: Vue 2 + Ant Design Vue + KlineCharts/ECharts
• Payment: USDT TRC20 on-chain (HD Wallet xpub derivation + TronGrid API)
• Mobile: Vue 3 + Capacitor (Android / iOS) — see QuantDinger-Mobile/
• Deployment: Docker Compose (with PostgreSQL)
• Current Version: V2.2.1 (Changelog)

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🔌 Supported Exchanges & Brokers

Cryptocurrency Exchanges (Direct API)

Exchange	Markets
Binance	Spot, Futures, Margin
OKX	Spot, Perpetual, Options
Bitget	Spot, Futures, Copy Trading
Bybit	Spot, Linear Futures
Coinbase Exchange	Spot
Kraken	Spot, Futures
KuCoin	Spot, Futures
Gate.io	Spot, Futures
Bitfinex	Spot, Derivatives

Traditional Brokers

Broker	Markets	Platform
Interactive Brokers (IBKR)	US Stocks	TWS / IB Gateway
MetaTrader 5 (MT5)	Forex	MT5 Terminal

Supported Markets

Market Type	Data Sources	Trading
Cryptocurrency	Binance, OKX, Bitget, + 100 exchanges	✅ Full support
US Stocks	Yahoo Finance, Finnhub, Tiingo	✅ Via IBKR
Forex	Finnhub, OANDA	✅ Via MT5
Futures	Exchange APIs	⚡ Data only

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Multi-Language Support

All UI elements, error messages, and documentation are fully translated. Language is auto-detected based on browser settings or can be manually switched in the app.

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🚀 Quick Start

Option 1: Docker (Recommended)

# 1. Clone & configure
git clone https://github.com/brokermr810/QuantDinger.git
cd QuantDinger
cp backend_api_python/env.example backend_api_python/.env

# 2. Edit .env — set your admin password & AI API key
#    ADMIN_USER=quantdinger
#    ADMIN_PASSWORD=your_password
#    OPENROUTER_API_KEY=your_key    (optional, for AI features)

# 3. Start all services
docker-compose up -d --build

Windows PowerShell: use Copy-Item backend_api_python\env.example -Destination backend_api_python\.env instead of cp.

That's it! Services will be available at:

Service	URL
Frontend UI	http://localhost:8888
Backend API	http://localhost:5000

Default login: quantdinger / 123456 (change in .env for production).

Common Docker Commands

docker-compose ps                  # View status
docker-compose logs -f backend     # View backend logs
docker-compose restart             # Restart services
docker-compose up -d --build       # Rebuild & restart
docker-compose down                # Stop services

Update to Latest Version

git pull && docker-compose up -d --build

Backup & Restore

# Backup database
docker exec quantdinger-db pg_dump -U quantdinger quantdinger > backup.sql

# Restore database
cat backup.sql | docker exec -i quantdinger-db psql -U quantdinger quantdinger

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Option 2: Local Development

Prerequisites: Python 3.10+, Node.js 16+, PostgreSQL 14+

# 1. Setup database
sudo -u postgres psql -c "CREATE DATABASE quantdinger; CREATE USER quantdinger WITH ENCRYPTED PASSWORD 'your_password'; GRANT ALL PRIVILEGES ON DATABASE quantdinger TO quantdinger;"
psql -U quantdinger -d quantdinger -f backend_api_python/migrations/init.sql

# 2. Start backend
cd backend_api_python
pip install -r requirements.txt
cp env.example .env              # Edit .env with your DATABASE_URL
python run.py                    # → http://localhost:5000

# 3. Start frontend (in another terminal)
cd quantdinger_vue
npm install
npm run serve                    # → http://localhost:8000

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Architecture

┌─────────────────────────────┐
│      quantdinger_vue         │
│   (Vue 2 + Ant Design Vue)   │
└──────────────┬──────────────┘
               │  HTTP (/api/*)
               ▼
┌─────────────────────────────┐
│     backend_api_python       │
│   (Flask + strategy runtime) │
└──────────────┬──────────────┘
               │
               ├─ PostgreSQL (multi-user, orders, membership)
               ├─ Redis (optional cache)
               ├─ TronGrid API (USDT payment verification)
               └─ Data providers / LLMs / Exchanges

Repository Layout

.
├─ backend_api_python/         # Flask API + AI + backtest + strategy + billing
│  ├─ app/
│  │  ├─ routes/               # API endpoints (user, billing, indicator, etc.)
│  │  └─ services/             # Business logic (trading, payment, community)
│  ├─ migrations/init.sql      # Database schema
│  ├─ env.example              # Copy to .env for configuration
│  └─ run.py                   # Entrypoint
├─ quantdinger_vue/            # Vue 2 UI (Ant Design Vue)
└─ QuantDinger-Mobile/         # Vue 3 + Capacitor mobile app (optional)

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Configuration (.env)

Use backend_api_python/env.example as a template. Key settings:

Category	Variables
Auth	SECRET_KEY, ADMIN_USER, ADMIN_PASSWORD
Database	DATABASE_URL (PostgreSQL connection string)
AI / LLM	LLM_PROVIDER, OPENROUTER_API_KEY, OPENAI_API_KEY, etc.
OAuth	GOOGLE_CLIENT_ID, GITHUB_CLIENT_ID, etc.
Security	TURNSTILE_SITE_KEY, ENABLE_REGISTRATION
Order Execution	ORDER_MODE (market/maker), MAKER_WAIT_SEC
Membership 🆕	MEMBERSHIP_MONTHLY_PRICE_USD, MEMBERSHIP_MONTHLY_CREDITS, MEMBERSHIP_YEARLY_PRICE_USD, etc.
USDT Payment 🆕	USDT_PAY_ENABLED, USDT_TRC20_XPUB, TRONGRID_API_KEY, USDT_ORDER_EXPIRE_MINUTES
Proxy	PROXY_PORT or PROXY_URL
Workers	ENABLE_PENDING_ORDER_WORKER, ENABLE_PORTFOLIO_MONITOR

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API

The backend provides REST endpoints for login, market data, indicators, backtesting, strategies, AI analysis, and billing.

• Health: GET /api/health
• Auth: POST /api/user/login, GET /api/user/info
• Billing: GET /api/billing/plans, POST /api/billing/usdt/create-order 🆕

For the full route list, see backend_api_python/app/routes/.

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License

Licensed under the Apache License 2.0. See LICENSE.

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🤝 Community & Support

• Contributing: Contributing Guide · Contributors
• Telegram: QuantDinger Group
• Discord: Join Server
• 📺 Video Demo: Project Introduction
• YouTube: @quantdinger
• Email: brokermr810@gmail.com
• GitHub Issues: Report bugs / Request features

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💼 Commercial License & Sponsorship

QuantDinger is licensed under Apache License 2.0 (code). However, Apache 2.0 does NOT grant trademark rights. Our branding assets (name/logo) are protected as trademarks and are governed separately from the code license:

• Copyright/Attribution: You must keep required copyright and license notices (including any NOTICE/attribution in the repo and in the UI where applicable).
• Trademarks (Name/Logo/Branding): Without permission, you may not modify QuantDinger branding (name/logo/UI brand), or use it to imply endorsement or misrepresent origin. If you redistribute a modified version, you should remove QuantDinger branding and rebrand unless you have a commercial license.

If you need to keep/modify QuantDinger branding in a redistribution (including UI branding and logo usage), please contact us for a commercial license.

See: TRADEMARKS.md

What you get with a Commercial License

• Commercial authorization to modify branding/copyright display as agreed
• Operations support: deployment, upgrades, incident support, and maintenance guidance
• Consulting services: architecture review, performance tuning, strategy workflow consulting
• Sponsorship options: become a project sponsor and we can display your logo/ad (README/website/in-app placement as agreed)

Contact

• Telegram: https://t.me/worldinbroker
• Email: brokermr810@gmail.com

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💝 Direct Support (Donations)

Your contributions help us maintain and improve QuantDinger.

Crypto Donations (ERC-20 / BEP-20 / Polygon / Arbitrum)

0x96fa4962181bea077f8c7240efe46afbe73641a7

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🎓 Supporting Partners

We are proud to be supported by academic institutions and organizations advancing quantitative finance education and research.

Quantitative Finance Society (QFS) Indiana University Bloomington Fostering the next generation of quantitative finance professionals

💡 Interested in becoming a supporting partner? We welcome collaborations with universities, research institutions, and organizations. Contact us at brokermr810@gmail.com or via Telegram.

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Acknowledgements

QuantDinger stands on the shoulders of great open-source projects:

Project	Description	Link
Flask	Lightweight WSGI web framework	flask.palletsprojects.com
flask-cors	Cross-Origin Resource Sharing extension	GitHub
Pandas	Data analysis and manipulation library	pandas.pydata.org
CCXT	Cryptocurrency exchange trading library	github.com/ccxt/ccxt
yfinance	Yahoo Finance market data downloader	github.com/ranaroussi/yfinance
akshare	China financial data interface	github.com/akfamily/akshare
bip-utils	HD wallet key derivation (BIP-32/44)	GitHub
Vue.js	Progressive JavaScript framework	vuejs.org
Ant Design Vue	Enterprise-class UI components	antdv.com
KlineCharts	Lightweight financial charting library	github.com/klinecharts/KLineChart
Lightweight Charts	TradingView charting library	github.com/nicepkg/lightweight-charts
ECharts	Apache data visualization library	echarts.apache.org
Capacitor	Cross-platform native runtime	capacitorjs.com

Thanks to all maintainers and contributors across these ecosystems! ❤️