docs: add docs with planning subdirectory for TODO features
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docs/planning/DOLPHIN_Period_Tracking_Feature_Analysis.md
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docs/planning/DOLPHIN_Period_Tracking_Feature_Analysis.md
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# DOLPHIN System Period Tracking Feature Analysis
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## Overview
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This document compiles all available information about adding 15m, 1H, and other period tracking capabilities to the DOLPHIN system, which currently tracks BULL% vs BEARS% in trade data.
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## Current DOLPHIN System Status
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Based on the conversation data found:
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### Existing Functionality
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- **Current Output**: Produces `up_ratio`/`down_ratio` based on 500 symbols
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- **Data Format**: JSON with regime ("BULL"/"BEAR"), ratios, timestamp
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- **Sample Data Shows**: Transitions like 76.3% bullish → 14.2% bullish (major regime shifts)
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- **Architecture**: Part of SILOQY = DOLPHIN (regime detection) + JERICHO (FSM signals) + future HARLEQUIN (trading)
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### Current Data Structure
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```json
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{
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"regime": "BULL",
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"up_ratio": 0.7627118644067796,
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"down_ratio": 0.23728813559322035,
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"total_symbols": 405,
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"timestamp": "2025-08-12T17:10:16.389625"
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}
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```
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## Proposed Period Tracking Enhancements
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### Missing Features Identified
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From the conversation analysis, the following enhancements were discussed:
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1. **Bollinger Band Distance Calculations**
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- Missing: BB distance calculations for BTC specifically
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- Need: BB proximity calculation as percentages
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- Proposed addition to data structure:
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```json
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{
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"bull_pct": 76.3,
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"bear_pct": 23.7,
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"regime": "BULL",
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"timestamp": "...",
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"bb_dist_pct": 1.23 // NEW: distance to closest BB
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}
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```
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2. **Time Period Tracking**
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- **3m candles**: Mentioned that "Jericho has been tested in Bitcoin 3m candles, yielding good results"
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- **Period synchronization**: DOLPHIN runs every ~5 seconds, JERICHO spec mentions 5-second SCANs
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- **Multi-timeframe support**: References to 15m, 1H periods for enhanced tracking
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3. **Historical Data Integration**
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- **Latest X Amount of Periods**: Need to track recent period performance
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- **Rolling Windows**: Implementation of moving averages across different timeframes
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- **Period-based Analysis**: Track bull/bear percentages across multiple timeframes simultaneously
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## Technical Implementation Requirements
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### Data Structure Enhancements
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The DOLPHIN system would need to expand its output to include:
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```json
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{
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"regime": "BULL",
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"current_period": {
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"up_ratio": 0.7627,
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"down_ratio": 0.2373,
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"timestamp": "2025-08-12T17:10:16.389625"
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},
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"period_tracking": {
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"5m": {
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"latest_periods": [
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{"up_ratio": 0.76, "down_ratio": 0.24, "timestamp": "..."},
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{"up_ratio": 0.72, "down_ratio": 0.28, "timestamp": "..."}
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],
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"average_bull_pct": 74.0,
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"trend": "BULLISH"
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},
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"15m": {
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"latest_periods": [...],
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"average_bull_pct": 71.5,
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"trend": "BULLISH"
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},
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"1H": {
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"latest_periods": [...],
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"average_bull_pct": 68.2,
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"trend": "NEUTRAL"
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}
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},
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"bb_analysis": {
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"btc_bb_distance_pct": 1.23,
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"proximity_status": "WATCHING"
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}
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}
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```
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### Integration Points
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1. **DOLPHIN → JERICHO**: Enhanced JSON websocket with regime/ratios + BB distances + period analysis
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2. **Period Synchronization**: Align DOLPHIN's ~5-second updates with JERICHO's 5-second SCANs
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3. **Multi-timeframe Analysis**: Support for 5m, 15m, 1H, and potentially longer periods
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## Proposed Feature Specifications
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### 1. Period Tracking Configuration
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- **Configurable Periods**: 5m, 15m, 30m, 1H, 4H, 1D
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- **History Depth**: Track latest X periods (configurable, default 20-50 periods)
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- **Rolling Calculations**: Moving averages of bull/bear percentages across periods
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### 2. Enhanced Analytics
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- **Trend Detection**: Identify bullish/bearish trends across different timeframes
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- **Momentum Analysis**: Rate of change in bull/bear percentages
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- **Cross-timeframe Correlation**: Identify when multiple timeframes align
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### 3. Alert System
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- **Regime Changes**: Alert when regime changes across multiple timeframes
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- **Threshold Breaches**: Configurable alerts for extreme bull/bear percentages
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- **Trend Reversals**: Early warning system for potential trend changes
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## Implementation Priority
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### Phase 1: Basic Period Tracking
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1. Add 15m and 1H period tracking to existing DOLPHIN output
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2. Implement rolling window calculations for latest X periods
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3. Basic trend detection (bullish/bearish/neutral)
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### Phase 2: Enhanced Analytics
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1. Cross-timeframe correlation analysis
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2. Momentum calculations and trend strength indicators
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3. Integration with JERICHO FSM for enhanced signal generation
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### Phase 3: Advanced Features
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1. Machine learning-based pattern recognition across periods
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2. Predictive analytics for regime changes
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3. Advanced alert and notification system
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## Notes and Limitations
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### Data Availability
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- Limited specific conversation data about exact implementation details
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- Most references are architectural rather than detailed specifications
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- Need more detailed requirements gathering for specific period tracking needs
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### Technical Considerations
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- **Performance Impact**: Adding multiple timeframe tracking will increase computational load
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- **Data Storage**: Need to consider storage requirements for historical period data
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- **Real-time Processing**: Ensure period calculations don't impact real-time performance
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## Recommendations
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1. **Start Simple**: Begin with 15m and 1H tracking as proof of concept
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2. **Configurable Design**: Make period selection and history depth configurable
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3. **Backward Compatibility**: Ensure existing DOLPHIN consumers continue to work
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4. **Performance Monitoring**: Implement metrics to monitor impact of new features
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5. **Gradual Rollout**: Phase implementation to validate each component before adding complexity
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## Missing Information
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The conversation dump did not contain detailed specifications for:
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- Exact calculation methods for period aggregation
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- Specific use cases for different timeframes
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- Performance requirements and constraints
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- Integration testing procedures
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- User interface requirements for period tracking data
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**Recommendation**: Conduct additional requirements gathering sessions to fill these gaps before implementation begins.
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