liuyu/nofx - nofx - Gitea: Git with a cup of tea

liuyu/nofx

Fork 0

mirror of https://github.com/NoFxAiOS/nofx.git synced 2026-07-09 14:00:57 +08:00

Commit Graph

Author	SHA1	Message	Date
tinkle-community	d4a5c0534d	Feature: Add position holding duration to AI decision context Track and display how long each position has been held to help AI make better timing decisions. Implementation: - Added UpdateTime field to PositionInfo struct (decision/engine.go:26) - Added positionFirstSeenTime map to AutoTrader for tracking (trader/auto_trader.go:60) - Record opening time when position is created successfully: - executeOpenLongWithRecord: Records timestamp for long positions (trader/auto_trader.go:540-541) - executeOpenShortWithRecord: Records timestamp for short positions (trader/auto_trader.go:593-594) - Fallback tracking in buildTradingContext for program restart scenarios (trader/auto_trader.go:386-392) - Auto-cleanup closed positions from tracking map (trader/auto_trader.go:409-414) - Display duration in user prompt with smart formatting: - Under 60 min: "持仓时长25分钟" - Over 60 min: "持仓时长2小时15分钟" Example Output: ``` 1. TAOUSDT LONG \| 入场价435.5300 当前价433.1900 \| 盈亏-0.54% \| 杠杆20x \| 保证金25 \| 强平价418.1528 \| 持仓时长2小时15分钟 ``` Benefits: - AI can see how long positions have been held - Helps enforce minimum holding period (30-60 min) from system prompt - Simple implementation with minimal overhead - Auto-cleanup prevents memory leaks Co-Authored-By: tinkle-community <tinklefund@gmail.com>	2025-10-29 14:20:40 +08:00
tinkle-community	00291617f1	Refactor: Enhance AI decision engine with Sharpe ratio optimization Major improvements to the AI trading decision engine: Core Changes in decision/engine.go (175 lines modified): 1. Sharpe Ratio Optimization Focus - Restructured system prompt to emphasize Sharpe ratio maximization - Added clear guidance: high-quality trades over frequent trading - Explained that 3-minute scan interval ≠ trade every cycle 2. Trading Frequency Controls - Defined optimal frequency: 2-4 trades/day (0.1-0.2 trades/hour) - Over-trading threshold: >2 trades/hour indicates issues - Minimum holding period: 30-60 minutes per position 3. Long/Short Balance Incentives - Emphasized equal profit potential for long and short positions - Removed long-bias with explicit short trading encouragement - Clear guidance: uptrend→long, downtrend→short, sideways→wait 4. Stricter Entry Signal Standards - Strong signals only: confidence ≥75, multi-indicator confirmation - Weak signals explicitly discouraged (single indicator, unclear trend) - Self-check mechanism to prevent premature re-entry (<30min) 5. Enhanced Sharpe Ratio Feedback Loop - Sharpe < -0.5: Stop trading for 6+ cycles (18min), deep reflection - Sharpe -0.5~0: Strict control, confidence >80 only - Sharpe 0~0.7: Maintain current strategy - Sharpe >0.7: Consider position size increase 6. Risk-Reward Ratio Validation - Added hard constraint: R:R must be ≥ 3.0:1 - Automatic calculation and validation in `validateDecision()` - Rejects trades with insufficient risk-reward ratio 7. Improved Prompt Structure - More organized sections with clear headers - Actionable guidance instead of abstract principles - Better examples for JSON output format Impact: These changes should significantly improve trading quality, reduce over-trading, and increase Sharpe ratio through better risk management and trade selection discipline. Co-Authored-By: tinkle-community <tinklefund@gmail.com>	2025-10-29 12:49:34 +08:00
tinkle-community	b2c6925c89	Refactor: Modularize codebase with separate decision and MCP packages Architecture improvements: - Extract AI decision engine to dedicated `decision` package - Create `mcp` package for Model Context Protocol client - Separate market data structures into `market/data.go` - Update trader to use new modular structure New packages: - `decision/engine.go` - AI decision logic and prompt building - `mcp/client.go` - Unified AI API client (DeepSeek/Qwen) - `market/data.go` - Market data type definitions Benefits: - Better separation of concerns - Improved code organization and maintainability - Easier to test individual components - More flexible AI provider integration - Cleaner dependency management Updated imports: - trader/auto_trader.go now uses decision and mcp packages - Consistent API across different AI providers Co-Authored-By: tinkle-community <tinklefund@gmail.com>	2025-10-29 06:14:57 +08:00

Author

SHA1

Message

Date

tinkle-community

d4a5c0534d

Feature: Add position holding duration to AI decision context

Track and display how long each position has been held to help AI make better timing decisions.
**Implementation**:
- Added UpdateTime field to PositionInfo struct (decision/engine.go:26)
- Added positionFirstSeenTime map to AutoTrader for tracking (trader/auto_trader.go:60)
- Record opening time when position is created successfully:
  - executeOpenLongWithRecord: Records timestamp for long positions (trader/auto_trader.go:540-541)
  - executeOpenShortWithRecord: Records timestamp for short positions (trader/auto_trader.go:593-594)
- Fallback tracking in buildTradingContext for program restart scenarios (trader/auto_trader.go:386-392)
- Auto-cleanup closed positions from tracking map (trader/auto_trader.go:409-414)
- Display duration in user prompt with smart formatting:
  - Under 60 min: "持仓时长25分钟"
  - Over 60 min: "持仓时长2小时15分钟"
**Example Output**:
```
1. TAOUSDT LONG | 入场价435.5300 当前价433.1900 | 盈亏-0.54% | 杠杆20x | 保证金25 | 强平价418.1528 | 持仓时长2小时15分钟
```
**Benefits**:
- AI can see how long positions have been held
- Helps enforce minimum holding period (30-60 min) from system prompt
- Simple implementation with minimal overhead
- Auto-cleanup prevents memory leaks
Co-Authored-By: tinkle-community <tinklefund@gmail.com>

2025-10-29 14:20:40 +08:00

tinkle-community

00291617f1

Refactor: Enhance AI decision engine with Sharpe ratio optimization

Major improvements to the AI trading decision engine:
**Core Changes in decision/engine.go** (175 lines modified):
1. **Sharpe Ratio Optimization Focus**
   - Restructured system prompt to emphasize Sharpe ratio maximization
   - Added clear guidance: high-quality trades over frequent trading
   - Explained that 3-minute scan interval ≠ trade every cycle
2. **Trading Frequency Controls**
   - Defined optimal frequency: 2-4 trades/day (0.1-0.2 trades/hour)
   - Over-trading threshold: >2 trades/hour indicates issues
   - Minimum holding period: 30-60 minutes per position
3. **Long/Short Balance Incentives**
   - Emphasized equal profit potential for long and short positions
   - Removed long-bias with explicit short trading encouragement
   - Clear guidance: uptrend→long, downtrend→short, sideways→wait
4. **Stricter Entry Signal Standards**
   - Strong signals only: confidence ≥75, multi-indicator confirmation
   - Weak signals explicitly discouraged (single indicator, unclear trend)
   - Self-check mechanism to prevent premature re-entry (<30min)
5. **Enhanced Sharpe Ratio Feedback Loop**
   - Sharpe < -0.5: Stop trading for 6+ cycles (18min), deep reflection
   - Sharpe -0.5~0: Strict control, confidence >80 only
   - Sharpe 0~0.7: Maintain current strategy
   - Sharpe >0.7: Consider position size increase
6. **Risk-Reward Ratio Validation**
   - Added hard constraint: R:R must be ≥ 3.0:1
   - Automatic calculation and validation in `validateDecision()`
   - Rejects trades with insufficient risk-reward ratio
7. **Improved Prompt Structure**
   - More organized sections with clear headers
   - Actionable guidance instead of abstract principles
   - Better examples for JSON output format
**Impact**: These changes should significantly improve trading quality,
reduce over-trading, and increase Sharpe ratio through better risk management
and trade selection discipline.
Co-Authored-By: tinkle-community <tinklefund@gmail.com>

2025-10-29 12:49:34 +08:00

tinkle-community

b2c6925c89

Refactor: Modularize codebase with separate decision and MCP packages

Architecture improvements:
- Extract AI decision engine to dedicated `decision` package
- Create `mcp` package for Model Context Protocol client
- Separate market data structures into `market/data.go`
- Update trader to use new modular structure
New packages:
- `decision/engine.go` - AI decision logic and prompt building
- `mcp/client.go` - Unified AI API client (DeepSeek/Qwen)
- `market/data.go` - Market data type definitions
Benefits:
- Better separation of concerns
- Improved code organization and maintainability
- Easier to test individual components
- More flexible AI provider integration
- Cleaner dependency management
Updated imports:
- trader/auto_trader.go now uses decision and mcp packages
- Consistent API across different AI providers
Co-Authored-By: tinkle-community <tinklefund@gmail.com>

2025-10-29 06:14:57 +08:00

3 Commits