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A-share low-frequency quantitative trading framework covering research, backtesting, and execution

Project description

DeltaFQ

ไธญๆ–‡ | English

Version Platform Python Build License

Python Open-source Quantitative Framework: Covering the full "Research, Backtest, Trade" lifecycle, building an industrial-grade closed-loop quantitative workflow from scratch to production.

Strategy Signals Backtest Overview

๐ŸŽ“ Official Tutorials

iMOOC - AI Quantitative System Course

Official Course: Deeply deconstructing the framework's architecture from 0 to 1, covering live trading logic and industrial-grade quantitative development. An essential course for mastering DeltaFQ.

๐Ÿ“ฆ Installation

pip install deltafq

For previous version source code, visit: https://pypi.org/project/deltafq/#history

โœจ Key Features

  • ๐Ÿ“ฅ Multi-source Data - Global multi-market historical/real-time data, ready to use
  • ๐Ÿง  Rapid Development - Signal-driven architecture, fast implementation with strategy templates
  • ๐Ÿ“‰ Professional Backtesting - High-performance matching engine, deep performance metrics and analysis
  • โšก Event-driven - Second-level market data distribution, millisecond-level Tick signal processing
  • ๐Ÿค– Live Gateway - Pluggable adapters, seamless switching between simulation and live trading

โšก Quick Start

import deltafq as dfq

# 1. Define strategy logic
class MyStrategy(dfq.strategy.BaseStrategy):
    def generate_signals(self, data):
        bands = dfq.indicators.TechnicalIndicators().boll(data["Close"])
        return dfq.strategy.SignalGenerator().boll_signals(data["Close"], bands)

# 2. Minimal backtest & results
engine = dfq.backtest.BacktestEngine()
engine.set_parameters("GOOGL", "2025-07-26", "2026-01-26")
engine.load_data()
engine.add_strategy(MyStrategy(name="BOLL"))
engine.run_backtest()
engine.show_report()
engine.show_chart(use_plotly=False)

๐Ÿš€ Application Example

DeltaFStation is an open-source quantitative trading cloud platform based on deltafq, integrating data services, strategy management, and trading access with paper and live support. Project: https://github.com/Delta-F/deltafstation/

DeltaFStation Architecture DeltaFStation Backtest Engine

๐Ÿ”Œ Interface Integration

  • [Data] yfinance โœ… - US, A-shares, HK, Crypto, Indices
  • [Data] eastmoney โœ… - OTC Funds (Index, QDII, Stock, Bond, Mixed)
  • [Data] miniQMT โœ… - A-share market data integration (see live trading section in the course)
  • [Trade] PaperTrade โœ… - Local simulation, tick-driven order matching, position and order management
  • [Trade] miniQMT Trade โœ… - A-share live trading (see live trading section in the course)

Minimal miniQMT live trade setup

from deltafq.live import LiveEngine

engine = LiveEngine(symbol="000001.SZ", signal_interval="1m")
engine.set_data_gateway("miniqmt", interval=3.0, mode="poll")
engine.set_trade_gateway(
    "miniqmt",
    userdata_mini_path=r"D:\BrokerQMT\userdata_mini",
    account_id="1234567890",
)

See details:

  • documents/LiveEngine.md
  • documents/MiniQmtTrade.md
  • documents/MiniQmtLiveEngine.md

๐Ÿ—๏ธ Project Architecture

deltafq/
โ”œโ”€โ”€ core/                          # Base classes, config, logging
โ”‚   โ”œโ”€โ”€ base.py
โ”‚   โ”œโ”€โ”€ config.py
โ”‚   โ””โ”€โ”€ logger.py
โ”œโ”€โ”€ data/                          # Fetch, clean, store, source mapping
โ”‚   โ”œโ”€โ”€ fetcher.py
โ”‚   โ”œโ”€โ”€ cleaner.py
โ”‚   โ”œโ”€โ”€ storage.py
โ”‚   โ”œโ”€โ”€ source_map.py
โ”‚   โ””โ”€โ”€ miniqmt_xtdata.py          # miniQMT / xtquant historical bars
โ”œโ”€โ”€ indicators/                    # Technical & fundamental factors
โ”‚   โ”œโ”€โ”€ technical.py
โ”‚   โ”œโ”€โ”€ fundamental.py
โ”‚   โ””โ”€โ”€ talib_indicators.py
โ”œโ”€โ”€ strategy/                      # Strategy base & signal generation
โ”‚   โ”œโ”€โ”€ base.py
โ”‚   โ””โ”€โ”€ signals.py
โ”œโ”€โ”€ backtest/                      # Backtest engine, metrics, reporting
โ”‚   โ”œโ”€โ”€ engine.py
โ”‚   โ”œโ”€โ”€ metrics.py
โ”‚   โ””โ”€โ”€ performance.py
โ”œโ”€โ”€ live/                          # Event engine, gateways, LiveEngine
โ”‚   โ”œโ”€โ”€ event_engine.py
โ”‚   โ”œโ”€โ”€ gateways.py                # DataGateway / TradeGateway abstractions
โ”‚   โ”œโ”€โ”€ gateway_registry.py        # Gateway factory & registry
โ”‚   โ”œโ”€โ”€ engine.py                  # LiveEngine orchestration
โ”‚   โ””โ”€โ”€ models.py                  # TickData, OrderRequest, โ€ฆ
โ”œโ”€โ”€ adapters/                      # Pluggable data / trade adapters
โ”‚   โ”œโ”€โ”€ data/                      # Data gateways (yfinance, miniQMT, โ€ฆ)
โ”‚   โ”‚   โ”œโ”€โ”€ yfinance_gateway.py
โ”‚   โ”‚   โ””โ”€โ”€ miniqmt_gateway.py
โ”‚   โ””โ”€โ”€ trade/                     # Trade gateways (Paper, miniQMT, โ€ฆ)
โ”‚       โ”œโ”€โ”€ paper_gateway.py
โ”‚       โ”œโ”€โ”€ miniqmt_client.py      # xttrader client wrapper
โ”‚       โ””โ”€โ”€ miniqmt_gateway.py     # Limit orders / cancel for LiveEngine
โ”œโ”€โ”€ trader/                        # Matching, orders, positions
โ”‚   โ”œโ”€โ”€ engine.py
โ”‚   โ”œโ”€โ”€ order_manager.py
โ”‚   โ””โ”€โ”€ position_manager.py
โ””โ”€โ”€ charts/                        # Signal, price & performance charts
    โ”œโ”€โ”€ signals.py
    โ”œโ”€โ”€ price.py
    โ””โ”€โ”€ performance.py
Project Architecture Workflow

๐Ÿค Contributing

  • Feedback: Bug reports and contributions are welcome via Issue or Pull Requests.
  • WeChat Official Account: Follow DeltaFQๅผ€ๆบ้‡ๅŒ– for updates, strategies, and quantitative resources.

WeChat Official Account

๐Ÿ“„ License

MIT License. See LICENSE for details.

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