How qusong0627/quantmind works
QuantMind is an AI-native quantitative research and trading platform spanning market data, factor discovery, model training and inference, backtesting, and simulated trading. The principal workflow begins in the desktop/web client, passes through backend services, and produces research signals, reports, or simulated orders. The README documents the end-to-end stages and product capabilities; source excerpts provide implementation evidence for selected simulation, backtesting, and storage components. Several README-described subsystems are represented at their supported directory paths because their internals were not sampled.
Main entry points: engine.py Simulation engine · data_platform Market data platform · backtest_service_query.py Qlib backtests · inference_backtest_service.py Batch inference
Components 21
User experience
- Desktop and web client
electron - Community model hub
backend/services/api/routers/hub_proxy.py
Research and intelligence
- News and sentiment
backend/services/api/news - Market analysis
backend/services/api/market_analysis - Research and screening
backend/services/api/routers/research.py - Factor evolution
alphaagent/components/coder/CoSTEER
Quant engines
- Model training
backend/services/engine - Batch inference
backend/services/engine/inference/inference_backtest_service.py - Qlib backtests
backend/services/engine/qlib_app/services/backtest_service_query.py - Backtest engine manager
backend/shared/backtest_engine/integration/engine_manager.py - Event-driven engine
backend/shared/backtest_engine/core/engine.py
Trading and risk
- Simulation engine
backend/services/simulation/engine.py - Order execution
backend/services/simulation/services/execution_engine.py - Orders and trade ledger
backend/services/simulation/models/order.py - Trading preflight and risk
backend/services/simulation/services/market_rules.py - Broker bridge
bridge/windows/src/api/routes.py
Platform services
- API services
backend/services/api - Market data platform
backend/services/engine/data_platform - Strategy storage
backend/shared/strategy_storage.py - Production monitoring
backend/shared/observability/logging.py
Other components
- Researcher / trader
Connections 28
- Researcher / trader → Desktop and web client: uses
- Desktop and web client → API services: requests services
- API services → Market data platform: serves data
- Market data platform → Research and screening: feeds screening
- Market data platform → News and sentiment: provides market context
- Researcher / trader → News and sentiment: monitors news
- Researcher / trader → Market analysis: reviews markets
- Researcher / trader → Research and screening: screens stocks
- Researcher / trader → Factor evolution: proposes hypotheses
- Factor evolution → Model training: produces factors
- Market data platform → Model training: provides features
backend/services/engine/inference/inference_backtest_service.py - Model training → Batch inference: supplies models
backend/services/engine/inference/inference_backtest_service.py - Batch inference → Qlib backtests: provides scores
- Researcher / trader → Qlib backtests: configures backtests
- Qlib backtests → Backtest engine manager: runs backtest
- Backtest engine manager → Event-driven engine: dispatches run
backend/shared/backtest_engine/integration/engine_manager.py - Researcher / trader → Strategy storage: manages strategies
- Strategy storage → Simulation engine: loads strategy
backend/services/simulation/engine.py - Batch inference → Simulation engine: supplies signals
- Researcher / trader → Trading preflight and risk: checks readiness
- Simulation engine → Market data platform: loads local bars
backend/services/simulation/engine.py - Simulation engine → Order execution: submits orders
backend/services/simulation/engine.py - Order execution → Orders and trade ledger: records fills
backend/services/simulation/services/execution_engine.py - Simulation engine → Trading preflight and risk: applies market rules
backend/services/simulation/engine.py - Researcher / trader → Community model hub: shares models
- API services → Community model hub: serves hub requests
- Researcher / trader → Broker bridge: connects broker
- Qlib backtests → Production monitoring: logs activity
backend/services/engine/qlib_app/services/backtest_service_query.py