Project Status & Development Roadmap

Last Updated: December 2025 Version: v1.0 - Production VoterAgent Ready Framework: Microsoft AutoGen 0.7.x

Project Overview

Human-in-loop algorithmic trading platform using Microsoft AutoGen framework with validated pure-math MACD+RSI strategies.

Core Philosophy: Pure mathematical indicators + human oversight > complex LLM sentiment analysis

Current Status: Production-ready VoterAgent with multi-agent framework in development

Current Status

✅ Production Ready (Phase 1 Complete)

Component	Status	Performance	Notes
VoterAgent	✅ Production	0.468 OOS Sharpe (QQQ)	Pure MACD+RSI voting. Note: 0.856 Sharpe was from older, less rigorous tests.
main.py CLI	✅ Functional	All 4 commands working	Fixed Oct 2025
Alpaca Integration	✅ Validated	Paper trading operational	35/35 tests passing
Position Management	✅ Complete	Broker-as-truth reconciliation	Real-time tracking
Order Management	✅ Complete	Bracket, stop, trailing orders	Full lifecycle support
Trading Cycle	✅ Optimized	90% fewer API calls	Cost-efficient batching
Market Data	✅ Complete	Alpaca + Polygon + Alpha Vantage	Multi-source with fallback
Documentation	✅ Complete	Restructured with numbering	Presentation-ready

🚧 Phase 2 Agents in Development (Nov 2025)

Component	Status	Notes
ScannerAgent	🚧 Implementation	Multi-ticker MACD+RSI scanning (#386)
RiskAgent	🚧 Implementation	Position sizing, circuit breaker (#387)
ExecutorAgent	✅ Complete	Trade execution, simulation mode (#388)
TradingOrchestrator	✅ Complete	Workflow management, state persistence (#389)
TradingPipeline	✅ Complete	Full 5-phase daily workflow orchestrator (#323)
Agent Factory & Bus	✅ Complete	Agent Bus infrastructure (#390) for pub-sub messaging
TrailingStopManager	✅ Complete	Progressive stop logic (#321)
GTT Triggers	✅ Complete	Persistent price triggers, multi-day trailing stops (#340)
Trading Modes	✅ Complete	Natural language risk modes (#400)
Human-in-Loop CLI	✅ Complete	Interactive trade approval interface with multiple execution modes

Branch Status: Core pipeline infrastructure complete. Phase 2 agent implementations in active refactoring. Architecture decision: using Agent Bus (#390) for inter-agent communication.

Development Roadmap

Phase 1: Core Trading System ✅ COMPLETE (Oct 2025)

Completed Components:

VoterAgent with validated MACD+RSI voting (OOS Sharpe 0.468)
Pure math calculations (no LLM dependencies)
Alpaca paper trading integration
Position and order management
Cost-efficient trading cycle (90% fewer API calls)
main.py CLI interface
Market data pipeline (Alpaca, Polygon, Alpha Vantage)
Comprehensive documentation restructure
Test coverage (35/35 passing)

Key Achievement: Production-ready VoterAgent with validated performance

Critical Bug Fixes:

Price validation for sub-penny rounding (Alpaca compliance)
SDK integration with OrderData object handling
Import issues and execute_lifecycle() method calls
Status checking for Alpaca enum formats
Robust error handling and fallback mechanisms

Phase 2: Multi-Agent System 🚧 IN PROGRESS (Q4 2025 - Q1 2026)

High Priority:

Human-in-Loop CLI (#308) - ✅ COMPLETE (Nov 2025)
- Interactive trade review interface
- Decision explanation and override capability
- Risk assessment display
- Multiple execution modes: CONFIRM, AUTO, PAPER, DISABLED
Complete Remaining Agents (#310) - ✅ IMPLEMENTATIONS COMPLETE, REFACTORING (Nov 2025)
- ScannerAgent: Multi-ticker MACD+RSI scanning (#386)
- RiskAgent: Position sizing and circuit breaker (#387)
- ExecutorAgent: Trade execution coordination (#388)
- TradingOrchestrator: Multi-agent workflow management (#389)
- Note: Refactoring to resolve Agent Bus integration collision

Medium Priority:

Agent Factory & Event Bus (#390) - 🚧 IN REFACTORING
- Centralized agent creation via AgentFactory singleton
- Pub-sub messaging via AgentBus for inter-agent communication
- 16 trading-specific EventType values
- Symbol filtering, TTL, correlation tracking
- Note: Event Bus (#397) duplicate rejected; using Agent Bus
Dynamic Trailing Stops (#321) - ✅ COMPLETE (Nov 2025)
- TrailingStopManager with progressive stop logic
- 2% breakeven, 4% lock 25%, 6% trail 50% profit
- Integrated into trade_lifecycle.py and trading_cycle.py
- Rate-limited to prevent API abuse
GTT Persistent Triggers (#340) - ✅ COMPLETE (Dec 2025)
- Persistent price triggers checked twice daily (scheduler)
- Conditions: price above/below, pct gain/loss, trailing stop, time window, volume
- Actions: alerts, order placement/cancellation via AlpacaOrderManager
- OCO groups for dual breakout/breakdown scenarios
- Multi-day trailing stop persistence via TrailingStopManager bridge
- 📁 Files: src/trading/gtt/ (manager, evaluator, executor, bridge)

Low Priority:

Forward Testing Protocol (#324) - ✅ COMPLETE (Nov 2025)
- 30-day validation framework with state persistence
- Performance metrics: Sharpe, win rate, drawdown, profit factor
- Daily/weekly/final reports with go/no-go recommendations
- Automated acceptance criteria validation
- Branch: feature/forward-testing-achat

Phase 2B: Multi-Account & Security 🚧 IN PROGRESS (Nov 2025)

Component	Status	Notes
Multi-Account Manager	✅ Complete	Account selection, API-first discovery (#401)
Security Architecture	📋 Planned	Credential management, OS keyring (#402)

#401 - Multi-Account Portfolio Management - ✅ COMPLETE:

✅ Account selection via CLI --account flag
✅ Natural language commands: "list accounts", "switch to account X"
✅ Agent tools: AutoGen-compatible function calls
✅ API-first discovery (Alpaca tells us account details)
✅ Automatic paper vs live detection
✅ Legacy single-account config backward compatibility
✅ 19 unit tests (all passing)
📁 Files: account_manager.py, account_commands.py, account_tools.py, accounts_config.py

#402 - Security Architecture (separate from #401):

OS Keyring integration for credential storage
Secure credential provider interface
Paper/live account isolation
Audit logging without credential exposure
TODO markers added in #401 code for future integration

Phase 3A: CLI & UX Improvements ✅ IN PROGRESS (Nov 2025)

Completed:

Pullback/Breakout Limit Orders (#344) - ✅ FIXED (Nov 28, 2025)
- Pullback orders now place LIMIT orders at 2.5% below current price
- Breakout orders place LIMIT orders at 1.5% above current price
- GTC (Good-Til-Canceled) ensures orders wait indefinitely
- Fixed execution manager to pass entry_limit_price for timing contexts
- Merged to feature/development Nov 28, 2025
Interactive Help System (#369) - ✅ COMPLETE
- /help command with category-based organization
- /help search KEYWORD for searchable documentation
- Command examples, aliases, related commands
- 23+ commands documented across 5 categories
- Merged to feature/development Nov 2025
Order Cancellation (#360) - ✅ COMPLETE (B-chat)
- cancel all orders with confirmation
- cancel order <id> with partial ID matching
- cancel <SYMBOL> orders for symbol-specific cancellation
- Merged to feature/development Nov 2025
Order Details Display (#348) - ✅ COMPLETE (B-chat)
- Natural language queries: "what is my stop level on META"
- Shows entry orders, stop/target orders, current price
- Calculates distance and percentage from entry
- Merged to feature/development Nov 2025

In Progress:

CLI FunctionTool Infrastructure (#433, #455, #456, #457, #458) - ✅ PHASE 2 COMPLETE (Dec 2025)
- ✅ Tool registry with 17 modular tool files (7287 lines total)
- ✅ cli_session.py reduced from 2800+ to 1657 lines
- ✅ Extracted: mode, timeframe, account, portfolio, order, scheduler, alert, execution_mode
- ✅ Additional: voter, backup, gtt, watchlist, trailing_stop, entry_planning, user_alert
- 🔜 Phase 3: CLI command integration for new tool groups
- 📁 Files: src/cli/tools/*.py (17 tool modules)
CLI Command Group Integration (#488, #489, #490) - ✅ COMPLETE (Dec 2025)
- #488: /voter commands for ranked voting management ✅
- #489: /timeframe multi-tf presets (trend_following, intraday, position) ✅
- #490: /backup commands for database management ✅
- All integrated in src/cli/commands/slash_commands.py
- Merged to feature/testing
Execution Mode Switching (#332)
- /toggle command for quick mode switching
- set execution-mode {confirm|auto|paper|disabled}
- Mode persistence and validation
- Target: Dec 2025
Config Externalization (#358)
- Move hardcoded values to config files
- Cleaner parameter management
- Easier testing and deployment
- Target: Q1 2026

Phase 3B: Signal Enhancement ⚠️ ON HOLD (Pending Research Resolution)

CRITICAL: GEX Research Contradiction Identified (Dec 2025)

The project's GEX research contains contradictory findings that must be resolved before proceeding:

Analysis Script	Finding	Optimal GEX Regime
`tsmom_vs_gex_analysis.py` (#421)	MACD+RSI performs best in positive gamma	POSITIVE_GAMMA
`tsmom_gex_hybrid.py` (#516)	Built on premise that TSMOM works best in negative gamma	NEGATIVE_GAMMA

#516 TSMOM+GEX Hybrid ✅ CLOSED (Hypothesis Invalidated)

Median improvement: -2.9% (hybrid performs WORSE than pure TSMOM)
The "inverse regime weighting" hypothesis is NOT validated
Script: scripts/research/tsmom_gex_hybrid.py

#518 MACD Parameter Stability ✅ CLOSED (No Robust Edge)

"Least Unprofitable" Parameters: fast+none with OOS Sharpe -0.223
Most MACD configs show IS→OOS decay (overfitting)
Script: scripts/research/macd_parameter_stability.py

#519 Transaction Cost Analysis ✅ CLOSED (MACD+RSI More Robust)

TSMOM: Avg Net Sharpe -0.259, 19% pass rate, 4 trades/yr
MACD+RSI: Avg Net Sharpe 0.173, 44% pass rate, 39 trades/yr
Script: scripts/research/transaction_cost_analysis.py

Recommended Actions Before Proceeding:

Resolve Research Contradiction - The two GEX analyses use different momentum definitions:
- tsmom_vs_gex_analysis.py uses MACD+RSI (short-term technical momentum)
- tsmom_gex_hybrid.py uses academic TSMOM (12-month return)
- These are fundamentally different strategies; results are not comparable
Standardize Strategy Definitions - Create canonical implementations:
- academic_tsmom - Sign of 12-month return (Moskowitz 2012)
- vol_scaled_tsmom - Volatility-scaled version
- technical_momentum - MACD+RSI voting
Validate GEX Hypothesis with Consistent Methodology - Re-run both analyses using the same strategy definition

Previously Planned (DEFERRED until resolution):

~~Integrate GEX as Regime Filter~~
~~Adopt S² Scaling for GEX~~
Implement Weekly KAMA as Trend Filter (Independent of GEX - can proceed)
- Finding: Weekly KAMA outperforms weekly MACD (avg Sharpe ~0.75).
- Action: Create a new TrendFilterAgent or add KAMA as a voter.
Timeframe Specification (#365)
- Multi-timeframe analysis for VoterAgent
- Better signal quality through timeframe confluence
Ranked Voter System (#364)
- Multi-indicator consensus voting
- Confidence scoring across multiple signals

Critical Research Gaps (Dec 2025)

The following simulation fidelity issues must be addressed before production deployment:

Gap	Issue	Impact	Resolution
Wick Risk	Vectorized backtests assume close-to-close holds	Overestimated Sharpe/Win rates (ignores intraday stop-outs)	Path-dependent simulation (#525)
Data Granularity	Some scripts estimate High/Low (close*1.01)	Cannot accurately simulate bracket orders in volatility regimes	Use actual OHLC data
Portfolio Correlation	Symbols analyzed in isolation	Diversification fails in negative gamma (correlations -> 1.0)	Portfolio-level simulation
Strategy Definitions	Multiple TSMOM/MACD definitions across scripts	Incoherent research narrative	Canonical implementations

#525 Path-Dependent Simulation: Created scripts/research/path_dependent_simulation.py to address wick risk. This engine checks SL/TP triggers intraday rather than assuming positions are held until close.

Phase 3C: Live Trading Preparation 🔜 PLANNED (Q2 2026+)

Future Enhancements:

JSON→YAML Conversion (#328)
- 40-50% token reduction for LLM feeds
- Optimize agent communication
- Cost savings on LLM calls
- Target: When implementing LLM-based agents
Live Trading Deployment
- Production credentials setup
- Enhanced monitoring dashboard
- Real-time alerting system
- Performance analytics
- Target: After human-in-loop CLI complete
Advanced Portfolio Analytics
- Multi-position performance tracking
- Risk-adjusted metrics
- Correlation analysis
- Drawdown reporting

Key Metrics

VoterAgent Performance (Validated 2024-2025)

Metric	Value	Benchmark
Sharpe Ratio	0.468 (OOS, QQQ)	>0.7 = Excellent
Total Return	36.6%	Outperformed SPY
Win Rate	51.4%	>50% target
Max Drawdown	-10.10%	<15% acceptable
Strategy	Pure MACD+RSI	No LLM sentiment

Note: The 0.856 Sharpe ratio from older tests has been superseded by more rigorous walk-forward validation results.

System Efficiency

Metric	Value	Improvement
API Calls/Day	10-15	90% fewer vs reactive
Cache Hit Rate	85%+	90%+ faster access
Response Time	<500ms	Real-time decisions
Test Coverage	313 passing	Priority 1-5 components (Issue #408 ✅)

Live Validation Results

Paper Trading:

Successfully placed 7 shares SPY @ $660 with bracket orders
Risk Management: 5% stop loss / 8% take profit confirmed operational
Fill Monitoring: Real-time order status tracking working
State Persistence: Position tracking across system restarts validated

Active Issues & Priorities

Critical Path (Must Complete for Production)

#308 - CLI Human-in-Loop Interface (P0 - ✅ COMPLETE)

Scope: User-initiated conversational trade assistant
Features: Natural language input, real VoterAgent analysis, entry/stop/target suggestions, GTC orders
Why Critical: Core design principle is human oversight
Status: ✅ 100% COMPLETE - MVP delivered and tested
Completed:
- Core interfaces, models, orchestrator
- LLMParser with OpenAI gpt-4o-mini + o4-mini
- RealVoterStrategy with production VoterAgent (0.856 Sharpe)
- SimpleRiskManager with portfolio % calculations
- AlpacaExecutionManager with bracket order support
- CLI presentation layer with interactive REPL
- Factory pattern with config.json integration
- Main integration (trade-assist command)
- All tests passing (8/8)
- Real API integration validated
Test Results:
- Natural language parsing: Working (3/3 tests)
- Real MACD+RSI analysis: Working (3/3 tests)
- SPY: SELL (65% conf), AAPL: BUY (65% conf)
Usage: python main.py trade-assist
Completed: November 8, 2025

#333 - Portfolio Manager Agent (P1 - ✅ PHASE 1 COMPLETE)

Scope: Risk management, position sizing, portfolio allocation checks
Features: Buying power checks, portfolio % limits, risk-based sizing, existing position handling
Why Important: Safe trading requires intelligent portfolio management
Depends On: #308 (needs basic trade interface first)
Phase 1 Status: ✅ COMPLETE (Nov 2025)
- PortfolioManager class with YAML configuration
- Pre-trade risk assessment (TradeAssessment)
- Portfolio allocation display
- Integration with PositionSizer (#416)
- 17 unit tests
Remaining Phases: Phase 2 (sector limits, correlation), Phase 3 (rebalancing)

High Priority (Multi-Agent System)

#310 - Complete Remaining AutoGen Agents

Why Critical: Multi-agent coordination needed for scale
Blocker For: Full system deployment
Components: Scanner, Risk, Executor, Orchestrator
Target: Q1 2026
Status: Placeholders exist

#331 - Multi-Agent Coordination & Debate System (P2 - NEW)

Scope: Agent collaboration patterns (sequential, group chat, voting)
Features: Multi-agent analysis, consensus building, dissenting opinions
Why Important: Enables sophisticated multi-perspective analysis
Depends On: #308, #310 (needs core agents implemented)
Target: Q1-Q2 2026
Status: Exploration phase, needs design discussion

#390 - Agent Factory & Event Bus ✅ COMPLETE (Nov 2025)

Scope: Centralized agent creation and pub-sub messaging infrastructure
Delivered: AgentFactory singleton, AgentBus pub-sub, 16 EventTypes
Features: Symbol filtering, TTL, correlation IDs, async wait_for_result()
Supersedes: #316 (closed)

Medium Priority (Feature Enhancements)

#330 - Options Analysis Support (P2 - NEW)

Scope: Options contracts analysis (Greeks, IV, OI)
Features: Call/put analysis, unusual activity detection, liquidity checks
Why Useful: Expands trading beyond commons
Depends On: #308 (commons version must work first)
Target: Q1 2026
Status: Data access validation needed (Alpaca options API)

#321 - Dynamic Trailing Stop Logic

Why Important: Enhanced profit protection
Integrates With: #308 (order lifecycle), #333 (risk management)
Target: Q1 2026

#332 - Autonomy Levels Expansion (P2 - NEW)

Scope: Expand beyond basic confirm/auto to conditional execution
Features: Per-ticker whitelists, conditional auto-execute, risk-based autonomy
Why Useful: Power users can delegate routine decisions
Depends On: #308 (Levels 0 & 1 must work first)
Target: Q2 2026
Status: Design phase

#324 - Forward Testing Protocol

Why Useful: Statistical validation before live trading
Depends On: #308 (needs human-in-loop CLI complete)
Target: Q2 2026

Low Priority (Optimization)

#328 - JSON→YAML Token Optimization

Why Useful: Cost reduction for LLM agents
Depends On: LLM-based agents active (#331)
Target: Q2 2026

Code Quality & Technical Debt

#409 - Refactor Complex Functions (C901 Warnings) (P2 - OPEN)

Scope: Break down complex functions in main.py
Target Functions: run_paper_trading_check() (26), main() (22)
Why Important: Improves testability and maintainability
Status: Currently blocking commits without --no-verify
Target: Q1 2026

#413 - Validate Test Coverage After Import Consolidation (P1 - OPEN)

Scope: Ensure recent import changes didn't break functionality
Coverage: Run full test suite with coverage metrics
Why Important: Import pattern changes may have subtle effects
Status: Test plan defined
Target: December 2025

See Code Quality Guide for detailed tracking and standards.

Completed

#327 - ✅ Make main.py Functional (COMPLETED Oct 2025)

Fixed all import errors
Validated Alpaca integration
All 4 commands working

#412 - Scripts Directory Import Audit - ✅ PARTIAL (Nov 29, 2025)

Audited all scripts in scripts/ directory
Fixed 2 research scripts with incorrect sys.path
Updated pyproject.toml with minimal targeted exclusions
Active utility scripts normalized, deprecated research preserved
Commit: b486c03
Files: config_usage_demo.py, generate_results_summary.py, pyproject.toml

#411 - Type Hints Assessment - ✅ ASSESSED (Nov 29, 2025)

Assessed Phase 1 core trading logic (5 files)
Found 85-90% type coverage already present
Determined current coverage is production-ready
Deferred further work until mypy is available
Files: voter_agent.py, position_manager.py, account_manager.py, trailing_stop_manager.py, unified_price_fetcher.py

#410 - Line Length Violations (E501) - ✅ COMPLETE (Nov 29, 2025)

Fixed 33 E501 line length violations across 5 files
Ran Black/isort formatters for auto-fixes
Manually split long f-strings and docstrings
All changes purely stylistic - no functional modifications
Commit: c0e9703
Files: alpaca_execution_manager, timeframe_tools, alpaca_trading_client, alpaca_market_data, daily_scheduler

Import Consolidation - ✅ COMPLETE (Nov 29, 2025)

Moved all inline imports to toplevel (C0415 resolved)
Added try/except wrappers for optional dependencies
Fixed import order across 10+ files
Commits: c77f407, 77f3a8b, 21c8df5
Files: main.py, alpaca_*, daily_scheduler, trading_pipeline, etc.

Architectural Decisions

What Works (Keep These)

1. Pure Math Over LLM Sentiment

MACD+RSI voting: 0.856 Sharpe (validated)
LLM sentiment: ~60% accuracy (deprecated)
Decision: VoterAgent uses pure calculations, no LLM

2. Human-in-Loop Design

System assists, humans decide
Not autonomous AI trading
Decision: Mandatory human approval for trades

3. Cost-Efficient Architecture

GTC orders reduce API calls 90%
Broker-as-truth prevents state drift
Decision: Batch operations, minimize API usage

4. Dual Model Configuration

gpt-4o-mini for tool calling (cheap, fast)
o3-mini for reasoning (better analysis)
Decision: Available for future agents (not used by VoterAgent)

What Doesn't Work (Avoid These)

1. LLM Sentiment Analysis

Extensively tested in V0-V4 framework
Performance inferior to pure math
Decision: Deprecated, archived for reference

2. Reactive Trading Systems

100+ API calls/day
Expensive, rate-limited
Decision: Proactive batching with GTC orders

3. Complex Multi-Indicator Ensembles

Diminishing returns beyond MACD+RSI
Over-optimization risk
Decision: Keep it simple, validated

Getting Started for Contributors

Quick Start (5 minutes)

# Clone and setup
git clone https://github.com/iAmGiG/AutoGen-TradingSystem.git
cd AutoGen-TradingSystem
conda create -n trading python=3.10
conda activate trading
pip install -e .

# Configure credentials in config/config.json
# Run test
python main.py test-voter

Development Areas (Prioritized)

Immediate Impact (Start Here):

Human-in-loop CLI (#308) - Core feature missing
RiskAgent implementation (#310) - Critical for safety
Dynamic stops (#321) - Profit protection

Nice to Have (Later): 4. Event bus (#316) - Scalability 5. Forward testing (#324) - Validation 6. YAML optimization (#328) - Cost reduction

Development Workflow

Check this document for current priorities
Review relevant GitHub issue
Follow code conventions in docs/03_reference/05_naming_conventions.md
Test in paper trading mode
Submit PR with validation results

Success Metrics

Technical Excellence

Sharpe ratio > 0.7 (achieved 0.856)
Win rate > 50% (achieved 51.4%)
Max drawdown < 15% (achieved 10.10%)
API efficiency > 80% reduction (achieved 90%)
Core test coverage 80%+ (313 tests passing - #408 ✅ CLOSED)

User Experience

CLI functional (main.py working)
Human-in-loop interface (in development)
Real-time position tracking (complete)
Interactive trade approval (planned)

System Reliability

Paper trading validated (SPY bracket orders working)
Broker reconciliation (operational)
Live trading deployed (pending human-in-loop)
Production monitoring (planned)

Lessons Learned

From V0-V4 Research (Deprecated Sentiment System)

What We Tested:

V0: Baseline MACD → 9.00% return
V1: News sentiment → 9.61% return (marginal improvement)
V2: VXX volatility → -3.53% return (contrarian failure)
V3: Blended approach → 1.04% return (too conservative)
V4: LLM reasoning → Variable (unreliable)

What We Learned:

LLM sentiment adds complexity without consistent value
Pure technical indicators (MACD+RSI) are more reliable
Simple validated strategies > complex unproven ones
Human oversight > autonomous AI trading

Current Approach:

VoterAgent: Pure MACD+RSI → 0.856 Sharpe (proven)
Human-in-loop: Humans make final decisions
Cost-efficient: 90% fewer API calls

Recent Milestones

November 2025 - Position Sizing & Portfolio Management (Nov 30, 2025)

Issue #415 - Approved Ticker List with Entry Modes (✅ COMPLETE)

Branch: feature/development (merged) Status: Implementation complete

Features Implemented:

TickerDatabase with SQLite backend
ApprovedTickersManager for ticker CRUD
Entry modes: buy, buy_add, watch_only, disabled
Per-ticker position limits
Leveraged ETF metadata and lookups
18 unit tests

Files Added:

src/trading/ticker_database.py (SQLite backend)
src/trading/approved_tickers.py (Manager class)
tests/unit/trading/test_approved_tickers.py

Issue #416 - Position Sizing Automation Phase 1 (✅ COMPLETE)

Branch: feature/development (merged) Status: Phase 1 complete

Features Implemented:

PositionSizer class for profile-based sizing
Conservative 5%, Moderate 10%, Aggressive 20% max positions
Per-ticker limit integration (#415)
Buying power validation
Existing position awareness
Risk calculation with stop prices
20 unit tests

Files Added:

src/trading/position_sizer.py
tests/unit/trading/test_position_sizer.py

Remaining Phases: Phase 2 (risk-based sizing), Phase 3 (smart sizing)

Issue #333 - Portfolio Manager Agent Phase 1 (✅ COMPLETE)

Branch: feature/portfolio-manager-333 Status: Phase 1 complete, ready for merge

Features Implemented:

PortfolioManager class with YAML configuration
Pre-trade risk assessment (TradeAssessment)
Portfolio allocation tracking and display
Buying power and exposure validation
Existing position warnings
Position count limits
Integration with PositionSizer (#416)
17 unit tests

Files Added:

src/trading/portfolio_manager.py
config_defaults/portfolio_config.yaml
tests/unit/trading/test_portfolio_manager.py

Remaining Phases: Phase 2 (sector limits, correlation), Phase 3 (rebalancing)

November 2025 - Advanced Trailing Stop Implementation (Nov 30, 2025)

Issue #414 - Advanced Trailing Stop Automation (✅ IMPLEMENTATION COMPLETE)

Branch: feature/trailing-stops-414 Status: Ready for integration testing

Features Implemented:

ClimbRate class with slow/medium/fast gain lock presets (20%-80% of gains)
TrailingStopConfig extended with volatility-aware parameters
ATR-based volatility adjustment (configurable multiplier)
Profit-zone tracking (enters profit protection at threshold)
Factory method: TrailingStopManager.from_mode_manager()
Mode-specific config in trading_modes.yaml

Climb Rate Gain Locking:

slow: 20%/40%/60% of gains
medium: 25%/50%/75% of gains (default)
fast: 33%/60%/80% of gains

Tests: 19 unit tests (all passing)

Next Steps:

Integrate into trading cycle scheduler (#323)
CLI command for trailing stop status (show trailing stops)
Documentation of CLI usage

Infrastructure Discovery (Unblocks #248):

replace_stop_order() already exists in src/trading/order_manager.py (lines 306-378)
Uses cancel-replace pattern (Alpaca's recommended approach)
TrailingStopManager already integrates at line 288
Partial exits (#248) can proceed using existing infrastructure

November 2025 - Partial Position Exits Implementation (Nov 30, 2025)

Issue #248 - Implement Partial Position Exits (✅ COMPLETE - MERGED)

Branch: feature/partial-exits-248 → Merged to feature/development Status: Implementation complete, merged, and tested

Features Implemented:

PartialExitManager class for multi-target position exits
Default 50/50 split: Target 1 (limit order) + Target 2 (trailing stop)
Per-mode configuration in trading_modes.yaml
Integration with TrailingStopManager for Target 2 dynamic stops
Comprehensive test coverage (21 tests, 90% coverage)
Research: Partial Exit Strategies

Configuration by Trading Mode:

Conservative: Target 1 at 4% profit
Moderate: Target 1 at 5% profit
Aggressive: Target 1 at 6% profit

Architecture:

ExitTarget dataclass for individual targets
PartialExitState for position tracking
Integration with OrderManager for limit orders
Integration with TrailingStopManager (#414) for trailing targets

Tests: 21 unit tests (all passing, 90% coverage)

Files Added:

src/trading/partial_exit_manager.py (143 lines)
tests/unit/trading/test_partial_exit_manager.py (21 tests)

Files Modified:

config_defaults/trading_modes.yaml (partial_exits config)
src/core/trading_modes.py (ModeParameters extended, get_partial_exit_config_dict())

Dependencies:

Leverages #414 (Advanced Trailing Stops) for Target 2
Uses #400 (Trading Modes) for per-mode configuration
Built on replace_stop_order() infrastructure from order_manager.py

Next Steps (Phase 2-4):

Integration with trading_cycle.py
CLI commands for manual position splitting (#424 - see below)
Per-ticker overrides via profile hierarchy

Commit: 05d7355 → Merged 9f710cd

November 2025 - Trailing Stop CLI Commands (Nov 30, 2025)

Issue #424 - Trailing Stop CLI Commands (✅ COMPLETE - MERGED)

Branch: feature/trailing-stop-cli-424 → Merged to feature/development Status: Implementation complete, merged, and tested

Features Implemented:

TrailingStopCommands class for CLI interface
show_trailing_stops() - Display all tracked positions with profit zones
show_config() - Show trailing stop configuration settings
set_manual_stop() - Manual stop price override with validation

CLI Commands Available:

show trailing stops / trailing stops status
- Lists positions with entry, current price, stop, profit %, zone status
- Shows climb rate, volatility settings, adjustment counts
trailing-stop config / show stop settings
- Displays mode, climb rate, progressive thresholds
- Shows volatility-aware settings (ATR multiplier)
set trailing-stop SYMBOL PRICE
- Manual stop override with broker integration
- Validates stop price range, updates broker order

Tests: 21 unit tests + integration test examples

Files Added:

src/cli/trailing_stop_commands.py (290 lines)
tests/unit/cli/test_trailing_stop_commands.py (21 tests)
tests/integration/cli/test_trailing_stops_integration.py (integration examples)

Dependencies:

#414 (Advanced Trailing Stop Automation) - backend complete
#400 (Trading Modes) - configuration foundation

Next Steps:

Register commands with CLI session natural language parser
Add trailing stop status to morning/evening reports

Commit: 68b7de2 → Merged to feature/development

November 2025 - Design Session & New Feature Issues (Nov 29, 2025)

Design Decisions Established:

Profile Hierarchy: Portfolio-level defaults → symbol-level overrides
Autonomy Gradient: Entry (approved list) → Exit (human-approved system) → Stops (auto) → Sizing (auto)
Killer Feature: Advanced trailing stops that protect profit once in profit zone
LLM Boundary: GEX tools for price levels, not pure guessing

New Issues Created & Completed:

#415 - Approved Ticker List with Entry Modes (✅ COMPLETE)
- Three modes: buy, buy_add, watchOnly, disabled
- SQLite backend for persistence
- Per-ticker position limits
- Leveraged ETF metadata
#416 - Position Sizing Automation (✅ PHASE 1 COMPLETE)
- Profile-based sizing (conservative/moderate/aggressive)
- Max portfolio % limits, per-symbol overrides
- Integration with #415 for per-ticker limits
- Phase 2-3 pending (risk-based, smart sizing)

November 2025 - Unit Testing Infrastructure (Issue #408) ✅ COMPLETE

Unit Test Suite (branch: feature/development - merged):

✅ 313 unit tests across Priority 1-5 components
✅ TradingPipeline: 25 tests (5-phase workflow, error handling, metrics)
✅ AlpacaTradingClient: 42 tests (order lifecycle, bracket orders, position queries)
✅ ExecutorAgent: 58 tests (trade execution, signal processing, risk limits)
✅ PositionManager: 42 tests (broker reconciliation, state management, edge cases)
✅ AccountCommands CLI: 17 tests (multi-account listing, switching, agent data)
✅ TimeframeCommands CLI: 23 tests (timeframe validation, recommendations)
✅ TradingCacheManager: 45 tests (SQLite cache operations, TTL, expiration)
✅ Existing Tests: 61 tests (indicators, VoterAgent, simple signals)
✅ Test fixtures in conftest.py (MockPosition, MockOrder, MockAccount)
✅ Module-level mocking for config_defaults dependencies

Files Created:

tests/unit/trading/test_trading_pipeline.py (25 tests)
tests/unit/trading/test_alpaca_trading_client.py (42 tests)
tests/unit/trading/test_position_manager.py (42 tests)
tests/unit/trading/test_executor_agent.py (58 tests)
tests/unit/cli/test_account_commands.py (17 tests)
tests/unit/cli/test_timeframe_commands.py (23 tests)
tests/unit/data_sources/test_sqlite_cache.py (45 tests)
tests/conftest.py (shared fixtures)

Run Tests:

python -m pytest tests/unit/ -v --no-cov

November 2025 - Trading Pipeline & Infrastructure Complete

TradingPipeline Implementation (branch: feature/trading-pipeline-323):

✅ Complete 5-phase daily workflow orchestrator (#323)
✅ Phase 1: Data Collection - Market hours validation, data freshness
✅ Phase 2: Analysis - VoterAgent MACD+RSI signal generation
✅ Phase 3: Execution - ExecutorAgent order placement with position sizing
✅ Phase 4: Management - PositionManager tracking (broker-as-truth)
✅ Phase 5: End-of-Day - Broker reconciliation, report generation
✅ Scheduled runner with configurable times (morning/afternoon/custom)
✅ Comprehensive integration tests (352 lines)
✅ Full documentation (README_PIPELINE.md - 466 lines)

Trading Modes Configuration (branch: feature/trading-modes-400):

✅ Natural language risk modes (#400) - "buy SPY aggressively"
✅ Conservative/Moderate/Aggressive presets in YAML
✅ Integration with LLMParser for natural language extraction
✅ No CLI flags - everything through conversational interface

TrailingStopManager (branch: feature/trailing-stops-321):

✅ Progressive stop logic (#321) - 2%/4%/6% profit thresholds
✅ Integration with trade_lifecycle.py and trading_cycle.py
✅ Rate-limited updates to prevent API abuse

Agent Bus Infrastructure (branch: feature/agent-bus-390):

✅ AgentBus pub-sub messaging system (#390)
✅ 16 trading-specific EventType values
✅ Symbol filtering, TTL, correlation tracking
✅ Supersedes #316 and #397 (duplicates closed)

Files Created:

src/trading/trading_pipeline.py (608 lines) - Main orchestrator
examples/run_trading_pipeline.py (174 lines) - CLI demo
examples/scheduled_pipeline_runner.py (299 lines) - Scheduled automation
src/trading/README_PIPELINE.md (466 lines) - Documentation
config_defaults/trading_modes.yaml - Risk mode configuration
src/core/trading_modes.py - TradingModeManager

November 2025 - Weekend Order Fix & Code Quality Improvements

Weekend Trading Enhancements (branch: feature/weekend-order-fix):

✅ Fixed off-hours bracket order validation failures
✅ Platform-aware emoji handling (Windows compatibility)
✅ Enhanced error detection using Alpaca API error codes (#377, #382)
✅ Extracted market hours configuration to YAML (#374, #379)
✅ Centralized user-facing messages to templates (#375, #380)
✅ Improved fallback handling for off-hours trading

Configuration Improvements:

Created market_hours.yaml with NYSE 2025 holiday calendar
Created cli_messages.yaml with 50+ message templates
Integrated MessageLoader for centralized message management
Platform-aware safe_print() utility for cross-platform symbols

Code Quality:

Error code-based validation (3-level detection: HTTP 422, Alpaca 4221xxxx, message patterns)
Backward-compatible YAML configuration loading
Message template system with fallback strings
4 commits, 6 issues resolved (#374, #375, #377, #379, #380, #382)

Documentation & Issue Organization:

Consolidated 7 folders into 4 organized sections
Added numerical sequencing (01-06 files)
Created 5 new consolidated documents
Removed "new" terminology throughout
Enhanced research_papers.md with abstract and introduction
Updated cross-references and navigation

GitHub Issue Cleanup:

Closed 20 obsolete/completed issues (42 → 23 open)
Created 4 new Phase 2 issues (#330, #331, #332, #333)
Updated all key issues with dependency relationships
Organized project board with priority/size/component fields
Simplified #308 to focused MVP scope

October 2025 - Production Ready

Fixed main.py CLI (all 4 commands working)
Validated Alpaca integration (35/35 tests passing)
Confirmed paper trading operational
Validated VoterAgent performance

September 2025 - Core Complete

VoterAgent production implementation
Complete order management system
Position tracking with broker reconciliation
Cost-efficient trading cycle
Comprehensive testing suite

Next Actions

Immediate (Next 2-4 Weeks) - P0 CRITICAL

#401 - Multi-Account Portfolio Management - ✅ COMPLETE:

✅ Account selection via --account CLI flag
✅ Natural language commands: "list accounts", "switch to account X"
✅ Agent tools for AutoGen function calls
✅ API-first discovery (Alpaca API tells us account details)
✅ Automatic paper vs live detection from API response
✅ Legacy single-account config backward compatibility
✅ Simple config-based credentials (security hardening in #402)
✅ 19 unit tests (all passing)
📁 Files: account_manager.py, account_commands.py, account_tools.py, accounts_config.py

Branch: feature/multi-account-401 - Ready for merge to feature/development

#323 - Trading Pipeline - ✅ COMPLETE:

✅ TradingPipeline 5-phase orchestrator
✅ VoterAgent integration for signal generation
✅ ExecutorAgent integration for order placement
✅ PositionManager broker-as-truth reconciliation
✅ Scheduled runner for automation
✅ Documentation and integration tests

Branch: feature/trading-pipeline-323 - Ready for merge

Next Priority - Complete Remaining Agent Implementations:

ScannerAgent (#386) - Multi-ticker screening
RiskAgent (#387) - Pre-execution validation, position limits
Integrate TrailingStopManager into pipeline management phase
Add RiskAgent validation to pipeline execution phase

Target: Q4 2025 completion → Unblocks full automated trading

Short Term (Q1 2026)

#333 - Portfolio Manager Agent ✅ PHASE 1 COMPLETE:

✅ PortfolioManager class with YAML configuration
✅ Pre-trade risk assessment with warnings
✅ Portfolio allocation display
✅ Integration with PositionSizer (#416)
Phase 2: Sector limits, correlation analysis
Phase 3: Rebalancing, volatility-adjusted sizing

#390 - Agent Factory & Event Bus ✅ COMPLETE:

✅ AgentFactory singleton with creator registration
✅ AgentBus pub-sub with symbol filtering
✅ 42 unit tests passing
✅ Orchestrator refactored to use factory/bus

#321 - Dynamic Trailing Stops:

Design stop adjustment algorithms
Integrate with order lifecycle management

Medium Term (Q1-Q2 2026)

#310 - Complete Remaining Agents: ✅ ALL COMPLETE

✅ Implement ExecutorAgent (order coordination) - COMPLETE (#388)
✅ Implement RiskAgent (position sizing, stop-loss) - COMPLETE (#387)
✅ Implement ScannerAgent (opportunity identification) - COMPLETE (#386)
✅ Build TradingOrchestrator (workflow management) - COMPLETE (#389)

#330 - Options Analysis (after #308 commons stable):

Validate Alpaca options data access
Build options-specific analysis (Greeks, IV, OI)
Extend CLI to accept options requests

#331 - Multi-Agent Coordination (after #310 complete):

Design coordination pattern (sequential vs group chat vs voting)
Implement agent debate/consensus system
Test multi-agent workflow with paper trading

Long Term (Q2 2026+)

Live Trading Deployment (after #308 + #324 complete):

Complete forward testing protocol (#324)
Configure production credentials
Set up monitoring dashboard
Deploy with initial capital allocation

#332 - Autonomy Expansion (after #308 L0/L1 stable):

Implement conditional auto-execute
Add per-ticker whitelists
Build rule-based autonomy system

This document tracks project status, roadmap, and development priorities. Updated monthly or after major milestones.

December 2025 - Code Quality Refactoring Sprint (Dec 2, 2025)

EPIC #436 - Code Quality Refactoring (✅ PHASE 1 COMPLETE)

Massive refactoring initiative to improve code organization, testability, and maintainability.

Issues Completed:

Issue	Description	Reduction	PR
#437	Extract validators from alpaca_trading_client.py	New modules	#448
#438	Split sqlite_cache.py by domain	65% (1386→474 lines)	#448
#440	Extract scheduler_cli.py components	69% (984→307 lines)	#449
#441	Extract validators from execution_manager	20% (985→785 lines)	#450
#442	Extract state/reporter from orchestrator	24% (958→728 lines)	#451
#425	In-house backtesting framework	New framework (~650 lines)	#452

New Modules Created:

Trading Validators (src/trading/validators/):
- order_validator.py - Order validation with provider injection
- enum_mappers.py - Centralized Alpaca enum mapping
- error_handling.py - API error extraction and formatting
- response_parsers.py - Account/Order/Position response parsing
- bracket_validator.py - Bracket order error detection
Cache Domain Separation (src/data_sources/cache/):
- base_cache.py - Base SQLite cache with shared logic
- ohlcv_cache.py - Focused OHLCV market data cache
Scheduler CLI (src/cli/scheduler/):
- message_loader.py - YAML message loading
- daemon_manager.py - Cross-platform daemon management
- config_editor.py - Interactive config editing
- monitor.py - Status/history/logs display
- setup_wizard.py - First-time setup flow
Trading Orchestrator (src/autogen_agents/):
- workflow_state_manager.py - State persistence/recovery
- workflow_reporter.py - Report generation
Backtesting Framework (src/backtesting/):
- backtest_engine.py - Main engine compatible with any signal generator
- portfolio.py - Position/cash tracking with commission modeling Phase 1 Refactoring Complete - All 4 files refactored:

✅ #437 - alpaca_trading_client.py (validators extracted)
✅ #438 - sqlite_cache.py (65% reduction)
✅ #439 - trading_cycle.py (59% reduction, 4 components extracted)
🚧 #433 - cli_session.py (FunctionTool architecture, in progress)

Issue #439 Results (PR #454, merged Dec 2):

trading_cycle.py: 1248 → 512 lines (59% reduction)
Created 4 new components:
- local_state_manager.py (140 lines) - JSON state persistence
- broker_state_cache.py (278 lines) - TTL-based caching
- state_reconciler.py (475 lines) - State reconciliation logic
- report_generator.py (251 lines) - Report formatting
Maintained full backward compatibility via property accessors

Issue #433 Progress (cli_session.py - 3024 lines):

Broken into 5 sequential sub-issues (#455-459)
✅ #455 - Tool infrastructure (Phase 1A complete, PR #463)
✅ #456 - Mode & timeframe tools (Phase 1B complete, PR #463)
✅ #457 - Display tools (Phase 1C complete, PR #464)
- Created portfolio_tools.py (470 lines) - Portfolio/position display
- Created account_display_tools.py (177 lines) - Account management
- 6 FunctionTools registered in PORTFOLIO_TOOLS and ACCOUNT_TOOLS categories
✅ #458 - Execution tools (Phase 1D complete, PR #465)
- Created order_tools.py - Order management (5 tools)
- Created scheduler_tools.py - Scheduler status (4 tools)
- Created alert_tools.py - Position alerts (4 tools)
- 13 FunctionTools registered in ORDER_TOOLS, SCHEDULER_TOOLS, and ALERT_TOOLS categories
- Refactored date_utils.py complexity issues
✅ #459 - Final integration (Phase 1E complete, PR #466)
- Integrated portfolio_tools.show_portfolio() into _handle_portfolio_request
- Integrated mode_tools functions into_handle_trading_mode_request
- Reduced cli_session.py from 3024 to 2879 lines (-145 lines)
- Pre-existing C901 complexity issues tracked in #436

CLI Folder Reorganization (Dec 2, 2025):

Reorganized src/cli/ folder into logical subdirectories for better maintainability:

src/cli/
├── commands/           # Natural language command handlers
│   ├── account_commands.py
│   ├── timeframe_commands.py
│   └── trailing_stop_commands.py
├── utils/              # CLI utility modules
│   ├── ticker_completer.py
│   ├── trading_tips.py
│   ├── help_system.py
│   └── decision_formatter.py
├── scheduler/          # Scheduler subsystem (existing)
├── tools/              # FunctionTool wrappers (existing)
├── scheduler_cli.py    # Main scheduler interface
└── cli_session.py      # Main CLI session (1916 lines, target <1500)

Changes Made:

Created commands/ subdirectory for command handler modules
Created utils/ subdirectory for utility modules
Moved 7 files to appropriate subdirectories
Updated all import paths across codebase
Removed unused example_tool.py
Updated test files with new import paths

api_error_translator.py - User-friendly error messages

Critical Bugs Fixed:

Fixed self.client.trading → self.client.trading_client (4 instances)
Removed duplicate cancel_order() method bypassing safety checks

Remaining from EPIC #436:

✅ #433 - cli_session.py FunctionTool architecture (COMPLETE - PRs #463-466)
#439 - trading_cycle.py extraction (deferred)

December 2025 - Research Initiatives

Issue #425 - Backtesting Framework (✅ COMPLETE)

In-house framework refactored from validated experiment_293
Validated: 0.856 Sharpe on AAPL 2024
CLI integration ready
Research paper structure (LaTeX) prepared

Issue #420 - TSMOM Research (🔜 NEXT - Assigned to B)

TSMOMSignalGenerator implemented (12-month momentum)
Ready for 2016-2024 validation experiments
Research paper in progress

Issue #501 - Big Data GEX Calculation Pipeline (✅ COMPLETE - Dec 18, 2025)

Vectorized pandas operations: 100-1000x speedup vs row-by-row
SQLite WAL optimization: 5-10x faster bulk inserts
Processed 50.88M options records -> 17,835 daily GEX metrics
Execution time: ~10 minutes total, ~1,700 records/second
Database: 34 symbols x 5+ years of daily GEX regimes
Production-ready with multiprocessing parallelization

Issue #421 - TSMOM vs GEX Analysis (✅ COMPLETE - Dec 18, 2025)

Analyzed 34 symbols across 5 asset classes
TSMOM Sharpe in positive gamma: 1.282 average
Key insight: 70% signal overlap, complementary indicators
Best performers: TNA (3.78), FAS (3.48), LABU (3.08)
Recommendation: Use GEX for position sizing, not signal filtering

Issue #496 - Cross-Asset Regime Correlation (✅ COMPLETE - Dec 18, 2025)

Equity: 81.9% positive gamma (stable)
Volatility: 32.8% positive gamma (inverted)
Bonds: 85.2% positive gamma (hedging utility)
UVXY leads SPY by 1 day (0.456 correlation)
Strategic implications: Cross-asset rotation signals

Documentation Delivered:

gex_pipeline_architecture.md (technical design, big data techniques)
tsmom_vs_gex_analysis.md (comparative signal analysis)
cross_asset_correlation.md (asset class regime relationships)
COMPLETION_SUMMARY.md (project milestones and findings)

December 2025 - Core Execution Features (Dec 14, 2025)

A Chat Stream - Execution Pipeline (branch: feature/core-execution)

Issue #366 - OHLCV-Based Intraday Entry Plan (COMPLETE)

Created src/trading/instruments/entry_planning.py
ATR-based stop-loss and take-profit calculation
Support/resistance detection using recent price extremes
Volume confirmation for entry quality scoring
Integrated into real_voter_strategy.py with fallback to percentage-based stops
Commit: 3bf530c

Files Added:

src/trading/instruments/entry_planning.py (~200 lines)

Files Modified:

src/trading/instruments/__init__.py (exports)
src/strategies/real_voter_strategy.py (integration)

Issue #372 - Multi-Level Price Targets (COMPLETE)

Created src/trading/orders/multi_level_targets.py
MultiLevelTargetManager class for 1-5 price target management
DistributionStrategy enum: equal, progressive, inverse, custom
ATR-based target calculation using OHLCV data
Order splitting capability for existing positions
Integration with PartialExitManager and TrailingStopManager
Commit: a3dbeac

Files Added:

src/trading/orders/multi_level_targets.py (~450 lines)

Files Modified:

src/trading/orders/__init__.py (exports)

Next: #414 KILLER Advanced Trailing Stop Automation

December 2025 - Code Grooming & Large File Refactoring (Dec 23, 2025)

Large File Refactoring - COMPLETED:

Issue	File	Before	After	Reduction	Status
#509	cli_session.py	1657	1018	38%	✅ CLOSED
#510	sqlite_cache.py	1587	947	40%	✅ CLOSED
#511	alpaca_trading_client.py	1568	1075	31%	✅ CLOSED
#512	scanner_agent.py	969	813	16%	✅ CLOSED
#513	date_utils.py	844	-	-	OPEN
#514	google_search_api.py	914	-	-	OPEN

New Modules Created:

#509 - IntentClassifier (src/cli/utils/intent_classifier.py)
- Extracted classify_intent() and resolve_ticker_with_llm() methods
- LLM-based intent classification with pattern matching fallback
#510 - Cache Mixins (src/cache/)
- options_cache.py - OptionsCacheMixin (329 lines)
- trade_cache.py - TradeCacheMixin (263 lines)
#511 - Advanced Orders (src/trading/broker/advanced_orders.py)
- AdvancedOrdersMixin with trailing stop, bracket, modify methods
#512 - Scanner Config (src/autogen_agents/agents/scanner_config.py)
- Config loaders, dataclasses (TierLimits, ScanConfig, ScanResult)

Commits:

4b40777 - refactor(#509): extract IntentClassifier from cli_session.py
094c920 - refactor(#510): extract options and trade cache mixins
76182fa - refactor(#511): extract advanced orders mixin
7d54640 - refactor(#512): extract scanner configuration

#521 - DRY Improvements & Code Quality Cleanup (✅ CLOSED):

Task	Module Created	Description
Error sanitization	`src/cli/utils/error_utils.py`	Shared `sanitize_error_message()` function
Platform UI utils	`src/cli/utils/ui_utils.py`	`get_error_prefix()`, `get_mode_indicator()`, `clear_screen()`
Magic constant	`RealVoterStrategy`	`MIN_REQUIRED_CANDLES = 42` with MACD derivation comment

Removed 4 instances of platform.system() == "Windows" checks
Fixed bug: Windows cls requires shell=True (shell built-in)
Commits: 361d849, 3134cdb

Other Large Files (700+ lines) for future consideration:

trailing_stop_manager.py (812) - Single class, focused
alpaca_execution_manager.py (784) - Has validators
db_backup.py (780) - Single class, utility
alerts_watchlists.py (738) - Could split
trading_orchestrator.py (723) - Could split
gtt_manager.py (712) - 4 classes
voter_tools.py (709) - FunctionTool pattern, ok

Branch: feature/testing

FilesExpand file tree

02_project_status.md

Latest commit

History

02_project_status.md

File metadata and controls

Project Status & Development Roadmap

Project Overview

Current Status

✅ Production Ready (Phase 1 Complete)

🚧 Phase 2 Agents in Development (Nov 2025)

Development Roadmap

Phase 1: Core Trading System ✅ COMPLETE (Oct 2025)

Phase 2: Multi-Agent System 🚧 IN PROGRESS (Q4 2025 - Q1 2026)

Phase 2B: Multi-Account & Security 🚧 IN PROGRESS (Nov 2025)

Phase 3A: CLI & UX Improvements ✅ IN PROGRESS (Nov 2025)

Phase 3B: Signal Enhancement ⚠️ ON HOLD (Pending Research Resolution)

CRITICAL: GEX Research Contradiction Identified (Dec 2025)

Critical Research Gaps (Dec 2025)

Phase 3C: Live Trading Preparation 🔜 PLANNED (Q2 2026+)

Key Metrics

VoterAgent Performance (Validated 2024-2025)

System Efficiency

Live Validation Results

Active Issues & Priorities

Critical Path (Must Complete for Production)

High Priority (Multi-Agent System)

#310 - Complete Remaining AutoGen Agents

#331 - Multi-Agent Coordination & Debate System (P2 - NEW)

#390 - Agent Factory & Event Bus ✅ COMPLETE (Nov 2025)

Medium Priority (Feature Enhancements)

#330 - Options Analysis Support (P2 - NEW)

#321 - Dynamic Trailing Stop Logic

#332 - Autonomy Levels Expansion (P2 - NEW)

#324 - Forward Testing Protocol

Low Priority (Optimization)

#328 - JSON→YAML Token Optimization

Code Quality & Technical Debt

#409 - Refactor Complex Functions (C901 Warnings) (P2 - OPEN)

#413 - Validate Test Coverage After Import Consolidation (P1 - OPEN)

Completed

#327 - ✅ Make main.py Functional (COMPLETED Oct 2025)

#412 - Scripts Directory Import Audit - ✅ PARTIAL (Nov 29, 2025)

#411 - Type Hints Assessment - ✅ ASSESSED (Nov 29, 2025)

#410 - Line Length Violations (E501) - ✅ COMPLETE (Nov 29, 2025)

Import Consolidation - ✅ COMPLETE (Nov 29, 2025)

Architectural Decisions

What Works (Keep These)

1. Pure Math Over LLM Sentiment

2. Human-in-Loop Design

3. Cost-Efficient Architecture

4. Dual Model Configuration

What Doesn't Work (Avoid These)

1. LLM Sentiment Analysis

2. Reactive Trading Systems

3. Complex Multi-Indicator Ensembles

Getting Started for Contributors

Quick Start (5 minutes)

Development Areas (Prioritized)

Development Workflow

Success Metrics

Technical Excellence

User Experience

System Reliability

Lessons Learned

From V0-V4 Research (Deprecated Sentiment System)

Recent Milestones

November 2025 - Position Sizing & Portfolio Management (Nov 30, 2025)

November 2025 - Advanced Trailing Stop Implementation (Nov 30, 2025)

November 2025 - Partial Position Exits Implementation (Nov 30, 2025)

November 2025 - Trailing Stop CLI Commands (Nov 30, 2025)

November 2025 - Design Session & New Feature Issues (Nov 29, 2025)

November 2025 - Unit Testing Infrastructure (Issue #408) ✅ COMPLETE

November 2025 - Trading Pipeline & Infrastructure Complete

November 2025 - Weekend Order Fix & Code Quality Improvements

October 2025 - Production Ready

September 2025 - Core Complete

Next Actions

Immediate (Next 2-4 Weeks) - P0 CRITICAL

Short Term (Q1 2026)