# Phase 55: Tax Loss Harvesting - Test Summary
## Build Status: ✅ COMPLETE
### Components Implemented
1. **Python Module**: `/home/quant/apps/quantclaw-data/modules/tax_loss_harvesting.py` (362 LOC)
- Portfolio scanning for TLH candidates
- Wash sale rule checking (30-day window)
- Tax savings estimation
- Sector replacement suggestions
2. **CLI Integration**: Updated `/home/quant/apps/quantclaw-data/cli.py`
- Registered 4 new commands
- Added help documentation
3. **API Route**: `/home/quant/apps/quantclaw-data/src/app/api/v1/tax-loss/route.ts` (123 LOC)
- 4 endpoints matching CLI functionality
4. **Service Registry**: Updated `/home/quant/apps/quantclaw-data/src/app/services.ts`
- Added 4 service definitions
5. **Roadmap**: Updated `/home/quant/apps/quantclaw-data/src/app/roadmap.ts`
- Phase 55 marked as "done" with 485 LOC
---
## Test Results
### 1. TLH Portfolio Scan ✅
```bash
python cli.py tlh-scan AAPL,TSLA,MSFT,AMZN,META
```
**Result**: Successfully identified 4 loss positions from 5 tickers:
- MSFT: -17.56% YTD (best TLH candidate)
- AMZN: -7.92% YTD
- TSLA: -6.55% YTD
- META: -1.71% YTD
- AAPL: Positive (excluded from results)
**Average loss**: -8.43%
---
### 2. Wash Sale Check ✅
```bash
python cli.py wash-sale-check TSLA 2026-02-25
```
**Result**:
- Calculated wash sale window: 2026-01-26 to 2026-03-27
- Days until safe to repurchase: 29 days
- Warning message properly displayed
---
### 3. Tax Savings Estimation ✅
```bash
python cli.py tax-savings TSLA --cost-basis 450 --shares 100
```
**Result**:
- Position: 100 shares @ $450 cost basis
- Current price: $409.38
- Capital loss: $4,062
- **Estimated tax savings: $1,015.50** (at 25% tax rate)
- Comprehensive next steps provided
---
### 4. Replacement Suggestions ✅
```bash
python cli.py tlh-replacements TSLA
```
**Result**:
- Identified sector: Consumer Cyclical
- Suggested 3 ETF replacements:
1. XLY (Consumer Discretionary SPDR)
2. FDIS (Fidelity Consumer Discretionary)
3. VCR (Vanguard Consumer Discretionary)
- All with current prices and YTD performance
- Proper wash sale avoidance guidance
---
## API Endpoints (Next.js)
All routes available at `/api/v1/tax-loss?action=<ACTION>¶ms`:
1. **Scan**: `?action=scan&tickers=AAPL,TSLA,MSFT`
2. **Wash Sale**: `?action=wash-sale-check&ticker=TSLA&date=2026-02-25`
3. **Tax Savings**: `?action=tax-savings&ticker=TSLA&cost_basis=450&shares=100&tax_rate=0.25`
4. **Replacements**: `?action=replacements&ticker=TSLA`
---
## Data Sources Used
- **Yahoo Finance**: Price history, YTD returns, sector classification
- **Built-in Mappings**: Sector classifications, ETF replacement catalog
- **Calculations**: IRS wash sale rules (30-day window), tax savings estimation
---
## Features Delivered
✅ **Portfolio Scanning**
- YTD return calculation from Jan 1
- Loss position identification
- TLH score ranking (biggest losses first)
- Sector classification
✅ **Wash Sale Protection**
- 30-day before/after window calculation
- Safe repurchase date
- Price history verification
- Warning system
✅ **Tax Savings Calculation**
- Capital loss quantification
- Tax savings at configurable rate (default 25%)
- Position analysis (cost basis vs current value)
- Actionable recommendations
✅ **Replacement Securities**
- Sector-matched ETF suggestions
- Current prices and YTD performance
- Wash sale avoidance strategy
- Multiple options per sector
---
## Lines of Code
- **Python Module**: 362 lines
- **TypeScript API**: 123 lines
- **Total**: 485 lines
---
## Integration Complete
✅ CLI registration in `cli.py`
✅ Service definitions in `services.ts`
✅ API route in `src/app/api/v1/tax-loss/route.ts`
✅ Roadmap updated to "done" status
✅ All 4 commands tested and working
---
## Next Steps for Users
1. **Scan your portfolio** for loss positions
2. **Estimate tax savings** on specific positions
3. **Check wash sale windows** before selling
4. **Find replacement securities** to maintain sector exposure
5. **Use tax savings** to rebalance portfolio
---
## Example Workflow
```bash
# 1. Scan portfolio for TLH candidates
python cli.py tlh-scan AAPL,TSLA,MSFT,AMZN,META,GOOGL,NVDA
# 2. Check wash sale window for a specific ticker
python cli.py wash-sale-check MSFT 2026-03-01
# 3. Estimate tax savings on the position
python cli.py tax-savings MSFT --cost-basis 471.86 --shares 50
# 4. Find replacement securities
python cli.py tlh-replacements MSFT
# 5. Execute strategy:
# - Sell MSFT (harvest $4,000 loss)
# - Wait 31 days
# - Buy XLK or VGT (Tech sector ETF)
# - Save ~$1,000 in taxes
```
---
**Build completed**: 2026-02-25
**Status**: Production-ready ✅
**Phase 55**: DONE 🎉
