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M2: Hedging & Portfolio Protection (v2.0) - Phases 2-9#10

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AojdevStudio merged 76 commits intomainfrom
gsd/phase-09-sqqq-vs-puts-comparison
Feb 18, 2026
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M2: Hedging & Portfolio Protection (v2.0) - Phases 2-9#10
AojdevStudio merged 76 commits intomainfrom
gsd/phase-09-sqqq-vs-puts-comparison

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Summary

Complete implementation of the M2 Hedging & Portfolio Protection milestone for Finance Guru v2.0. This PR consolidates 76 commits across Phases 3-9, delivering the full hedging toolkit, total return analysis, and onboarding system.

Phase Breakdown

Phase 03 - Onboarding Wizard

  • Pydantic state model and validation utilities
  • 8 section runner functions for interactive onboarding
  • Wizard CLI entry point with config generation
  • Comprehensive test suite for onboarding stack

Phase 04 - Onboarding Polish & Hook Refactoring

  • Direct Bun .ts hook invocation, removed dead .sh wrappers
  • Performance test suite (all 3 hooks < 500ms)
  • Save/resume logic for onboarding wizard with tests

Phase 05 - Agent Readiness Hardening

  • Ruff linter/formatter replacing Black
  • GitHub issue/PR templates, CODEOWNERS, CI workflow
  • Pre-commit hooks (ruff, mypy, gitleaks, hygiene)
  • Core test coverage for analysis and utility calculators
  • Coverage enforcement in pre-commit, pytest, and CI

Phase 06 - Config Loader & Shared Hedging Models

  • Hedging domain models (HedgePosition, RollSuggestion, HedgeSizeRequest)
  • Total return models (TotalReturnInput, DividendRecord, TickerReturn)
  • HedgeConfig model and load_hedge_config() bridge
  • TDD test suites with YAML fixtures and override chain

Phase 07 - Total Return Calculator

  • TotalReturnCalculator with DRIP and data quality validation
  • Total return CLI with verdict display, league table, and DRIP comparison
  • CLI integration tests and CLAUDE.md tool reference updates

Phase 08 - Rolling Tracker & Hedge Sizer

  • RollingTracker calculator with position management
  • HedgeSizer calculator with sizing, allocation, and budget validation
  • Rolling tracker CLI with argparse subcommands
  • Hedge sizer CLI with contract sizing and budget validation
  • CLI integration tests and known-answer tests

Phase 09 - SQQQ vs Puts Comparison

  • Hedge comparison Pydantic models
  • HedgeComparisonCalculator with SQQQ simulation and put pricing
  • Hedge comparison CLI (Layer 3)
  • 15 known-answer tests for hedge comparison
  • M2 hedging components architecture diagram

Stats

  • 76 commits across 8 phases
  • 238 files changed (+30,145 / -7,708)
  • 24 feature commits, 17 test commits, 35 docs commits

Type of Change

  • Feature
  • Documentation
  • Refactoring

Test Plan

  1. Run uv run pytest to verify all tests pass
  2. Run uv run pytest --cov to verify coverage thresholds
  3. Run uv run ruff check . to verify lint passes
  4. Run uv run mypy src/ to verify type checking
  5. Verify CLI tools work: uv run python src/analysis/total_return_cli.py SPY --days 90
  6. Verify hedge comparison: uv run python src/analysis/hedge_comparison_cli.py SQQQ --days 90

Checklist

  • Tests passing locally
  • No merge conflicts with main
  • Documentation updated
  • Coverage enforcement active
  • Pre-commit hooks configured
  • CI workflow added

Co-Authored-By: AOJDevStudio

AojdevStudio and others added 30 commits February 5, 2026 18:54
- OnboardingState model with 8-section SectionName enum for wizard progress tracking
- validate_currency: parses $10,000.50, 25k, 1.5M formats
- validate_percentage: parses 4.5% to 4.5 with 0-100 range check
- validate_positive_integer: strict positive integer parsing
- ask_with_retry: 3-retry-then-skip wrapper using questionary.confirm
- Install questionary dependency (2.1.1)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- run_liquid_assets_section: cash, accounts, yield, structure
- run_investments_section: portfolio value, brokerage, retirement, allocation, risk
- run_cash_flow_section: income, expenses, savings, investment capacity
- run_debt_section: mortgage, student loans, auto loans, credit cards, weighted rate
- run_preferences_section: philosophy, focus areas, emergency fund months
- run_broker_section: brokerage name with pre-fill from investments, CSV guidance
- run_env_setup_section: user name, language, API keys (all optional)
- run_summary_section: formatted review with confirm/restart/defer flow
- All sections use ask_with_retry for validated prompts
- Enum fields stored as raw strings; conversion deferred to Plan 02

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Task 1: Onboarding models and retry-with-skip validators
- Task 2: Eight section runner functions

SUMMARY: .planning/phases/03-onboarding-wizard/03-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- 8-section orchestration via SECTION_ORDER with all section runners
- convert_state_to_user_data with string-to-enum mapping (_safe_enum)
- Config files to correct paths: private files to fin-guru-private/,
  CLAUDE.md and .env to project root, mcp.json to .claude/
- Backup existing files before overwriting (.backup extension)
- argparse entry point with --dry-run flag
- KeyboardInterrupt handled gracefully
- pytest-mock added as dev dependency

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- configPath: fin-guru/ -> fin-guru-private/fin-guru/config.yaml
- profilePath: fin-guru/ -> fin-guru-private/fin-guru/data/user-profile.yaml
- systemContextPath: fin-guru/ -> fin-guru-private/fin-guru/data/system-context.md

Fixes ONBD-17: agents now read profile from the location the
onboarding wizard writes to, completing the runtime chain:
wizard generates -> hook loads -> agents see user_name

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- test_onboarding_validators.py (34 tests): currency/percentage/integer
  parsing, ask_with_retry retry logic, skip-after-max, Ctrl+C handling
- test_onboarding_sections.py (11 tests): mocked questionary for liquid
  assets, investments, cash flow, preferences, env setup, summary;
  verifies strings stored for enum fields (not enum instances)
- test_onboarding_wizard.py (18 tests): state-to-model conversion with
  string-to-enum mapping, config file generation to correct paths,
  backup of existing files, unknown enum fallback, SECTION_ORDER structure

All 63 new tests pass. Full suite: 426 passed, 2 skipped, 0 failures.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 4/4
- Wizard CLI entry point with config generation
- Fix hook profile path for runtime agent loading
- Comprehensive test suite (63 new tests)
- Agent genericization verified (no changes needed)

SUMMARY: .planning/phases/03-onboarding-wizard/03-02-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…ate CONFIG.md

- Recreate .claude/settings.json with all 3 hooks calling .ts directly via bun run
- Delete skill-activation-prompt.sh (6-line bash wrapper, replaced by direct .ts)
- Delete post-tool-use-tracker.sh (177-line bash original, replaced by .ts port)
- Update CONFIG.md: all examples now reference .ts files with TypeScript syntax
- Stop hooks remain .sh (stop-build-check-enhanced.sh, error-handling-reminder.sh)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
… < 500ms

- Add test_hook_performance.test.ts with timeHook() helper for wall-clock measurement
- Warmup test primes Bun transpile cache before timed assertions
- load-fin-core-config.ts, skill-activation-prompt.ts, post-tool-use-tracker.ts all < 500ms
- 4 new tests, 86/87 total pass (1 pre-existing failure unrelated to this change)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Update settings.json, delete dead .sh files, update CONFIG.md
- Write Bun performance test suite for all 3 hooks

SUMMARY: .planning/phases/04-onboarding-polish-hook-refactoring/04-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- SIGINT handler + atexit safety net for Ctrl+C interrupt handling
- Atomic progress file save (tempfile + rename) after each section
- Resume detection on startup with questionary.confirm prompt
- Progress file cleanup on successful wizard completion
- WizardInterruptHandler class with two-layer safety net
- .onboarding-progress.json already gitignored (added in prior phase)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- 12 new tests covering save, load, delete, and integration scenarios
- TestSaveProgress: valid JSON creation, round-trip, atomic write safety
- TestLoadProgress: saved state, missing file, corrupt JSON, invalid schema
- TestDeleteProgress: file removal and no-op when missing
- TestWizardSaveResume: saves on interrupt, resumes from progress, deletes on completion
- Full regression suite: 438 passed, 2 skipped, 0 failed

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Add save/resume logic to onboarding wizard
- Write save/resume tests and run full regression suite

SUMMARY: .planning/phases/04-onboarding-polish-hook-refactoring/04-02-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 05: Agent Readiness Hardening
- Implementation decisions documented
- Phase boundary established

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 5: Agent Readiness Hardening
- Standard stack identified (ruff, pre-commit, pytest-cov, gitleaks, mypy)
- Architecture patterns documented (pyproject.toml config, hook coexistence with bd)
- Pitfalls catalogued (26% coverage vs 80% target, D rule conflicts, bd hook chain)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 05: Agent Readiness Hardening
- 5 plan(s) in 3 wave(s)
- 2 parallel (wave 1), 1 sequential (wave 2), 2 sequential (wave 3)
- Ready for execution
- Add complete ruff config to pyproject.toml (lint + format)
- Replace black>=24.10.0 with ruff>=0.12.0 in dev deps
- Enable rule categories: E, F, I, UP, W, B, SIM, C90, N, D
- Set Google-style pydocstyle convention
- Run uv sync to update lockfile

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Bug report YAML form with description, steps, expected/actual behavior, dropdowns
- Feature request YAML form with problem statement, proposed solution, alternatives
- PR template with summary, test plan, and review checklist sections

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- CODEOWNERS routes all reviews to @AojdevStudio
- CI workflow: ruff lint, ruff format, mypy, pytest with coverage
- Triggers on push/PR to main with concurrency cancellation
- Coverage threshold at 0 initially (TODO for plan 05-05 to raise to 80)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Create GitHub issue and PR templates
- Create CODEOWNERS and CI workflow

SUMMARY: .planning/phases/05-agent-readiness-hardening/05-02-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Auto-fix: import sorting, f-string cleanup, type upgrades, simplifications
- Format: 79 files reformatted to ruff style (double quotes, 88 char lines)
- Manual fixes: bare excepts -> specific types, raise from chaining,
  zip strict params, nested if collapsing, ambiguous var names
- noqa annotations for C901 complex CLI format functions (12 instances)
- Config tuning: ignore D205/D100/D107/B028/E402 (low-value for this codebase)
- All 438 tests pass with zero regressions

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Add ruff config to pyproject.toml and remove black
- Run one-time ruff lint and format cleanup

SUMMARY: .planning/phases/05-agent-readiness-hardening/05-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…ene hooks

- .pre-commit-config.yaml with 4 hook repos (pre-commit-hooks, ruff, mypy, gitleaks)
- mypy config in pyproject.toml with standard mode and third-party overrides
- Per-module relaxed overrides for existing financial codebase type issues
- Fix callable type annotation in onboarding_wizard.py (was using builtin callable)
- Auto-fix trailing whitespace and EOF issues across 35 files via hygiene hooks
- Exclude template YAML files, fin-guru-private/, tests/ from strict checks

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add install_pre_commit_hooks() function after Python deps step
- Auto-installs pre-commit via uv tool if not available
- Uses default migration mode to preserve bd hooks as .legacy
- Bump TOTAL_STEPS from 5 to 6 for progress tracking
- Install pre-commit hooks locally (bd hooks backed up)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Create .pre-commit-config.yaml and add mypy config
- Integrate pre-commit install into setup.sh

SUMMARY: .planning/phases/05-agent-readiness-hardening/05-03-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…um, volatility, correlation)

- 85 tests across 4 new/updated test files with synthetic data
- risk_metrics: VaR, CVaR, Sharpe, Sortino, max drawdown, Calmar, beta/alpha
- momentum: RSI, MACD, Stochastic, Williams %R, ROC, calculate_all
- volatility: Bollinger Bands, ATR, historical vol, Keltner, regime
- correlation: Pearson/Spearman matrix, covariance, diversification, rolling
- Fix: correlation.py rolling dates handle both datetime and date index types

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…et_data)

- 19 moving average tests: SMA/EMA/WMA/HMA known-answers, crossover detection, price position
- 13 market data tests: yfinance mocking, Finnhub realtime, fallback behavior, input normalization
- Total new tests across plan: 117 (85 analysis + 32 utility)
- Coverage: 35% (up from 26%), core modules 86-99%

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Task 1: Analysis calculator tests (risk_metrics, momentum, volatility, correlation)
- Task 2: Utility calculator tests (moving_averages, market_data)

SUMMARY: .planning/phases/05-agent-readiness-hardening/05-04-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
AojdevStudio and others added 26 commits February 17, 2026 21:37
…ty validation

GREEN phase: all 39 tests pass

- TotalReturnCalculator with calculate_price_return(), calculate_dividend_return(),
  calculate_total_return(), calculate_drip_return(), calculate_annualized_return()
- DividendDataError exception when data has gaps and force=False
- validate_dividend_data() with 25% tolerance, split artifact >3x median detection
- load_dividend_schedules() reads from fin-guru-private/dividend-schedules.yaml
- TotalReturnResult dataclass wraps TickerReturn with annualized, DRIP, breakdown
- Annualized return uses calendar days (365), not trading days (252)
- Imports DividendRecord, TotalReturnInput from src.models.total_return_inputs

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Task 1: Create dividend schedules YAML and write failing tests (RED)
- Task 2: Implement TotalReturnCalculator to pass all tests (GREEN)

SUMMARY: .planning/phases/07-total-return-calculator/07-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
… and DRIP comparison

- Layer 3 CLI with argparse: tickers (nargs+), --days, --output, --force, --save-to, --realtime
- fetch_ticker_data() uses yf.Ticker().history() for raw Close + Dividends
- Finnhub real-time price integration via get_prices() with graceful fallback
- Portfolio CSV auto-read from notebooks/updates/Portfolio_Positions_*.csv
- Human output: DRIP/non-DRIP side-by-side, verdict narrative, dollar amounts, period breakdown
- League table ranks tickers by total return with "Price misleading" indicators
- JSON output with verdict and dollar_impact fields
- DividendDataError catch with --force hint
- Educational disclaimer in all output
- Complete --help with usage examples and agent use cases
…rence

- TestCLIArgParsing: help, single/multi ticker, json output, force, realtime, save-to
- TestPortfolioCSVReader: load shares from temp CSV, missing CSV, latest CSV selection
- TestVerdictFormatting: sign-flip verdict, league table ranking, disclaimer, JSON validity
- TestFinnhubIntegration: graceful fallback on exception, not called without --realtime
- CLAUDE.md: Total Return added to Financial Analysis Tools table (9/11 complete)
- CLAUDE.md: Total Return added to Agent-Tool Matrix for Market Researcher, Quant Analyst, Strategy Advisor
Tasks completed: 2/2
- Create total_return_cli.py with all presentation features
- Add CLI integration tests and update CLAUDE.md tool reference

SUMMARY: .planning/phases/07-total-return-calculator/07-02-SUMMARY.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
… and budget validation

- calculate_contract_count: floor(portfolio_value / ratio) formula (HS-01)
- allocate_contracts: weight-based distribution with remainder to highest-weight
- read_portfolio_value_from_csv: Fidelity balance CSV parser
- HedgeSizer.resolve_portfolio_value: CLI flag -> CSV -> error cascade
- HedgeSizer.calculate: sizing, allocation, notional coverage
- HedgeSizer.validate_budget: live premium scan with over-budget warning (no scale-down)
- 43 unit tests covering all methods with synthetic data

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…ment

- RollingTracker class with get_status, suggest_rolls, log_roll, get_history
- scan_chain_quiet wrapper suppresses stderr from options chain scanner
- price_american_put applies intrinsic value floor to BS pricing (BS-01)
- Auto-archives expired positions on get_status()
- Graceful fallback when BS validation fails for deep ITM puts
- 36 unit tests with full mocking (no API calls)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 1/1
- HedgeSizer calculator with sizing, allocation, and budget validation

SUMMARY: .planning/phases/08-rolling-tracker-hedge-sizer/08-02-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 1/1
- RollingTracker calculator with get_status, suggest_rolls, log_roll, get_history

SUMMARY: .planning/phases/08-rolling-tracker-hedge-sizer/08-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tasks completed: 2/2
- Hedging knowledge base files (hedging-strategies.md, options-insurance-framework.md)
- Four agent definitions updated with knowledge file references

SUMMARY: .planning/phases/08-rolling-tracker-hedge-sizer/08-05-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…dation

- Standard flat argparse CLI matching 15+ existing CLIs
- --portfolio, --underlyings, --ratio, --budget, --output, --skip-budget flags
- Human output shows allocation table, coverage ratio, budget analysis
- JSON output with structured envelope format
- Portfolio value cascade: CLI flag > Fidelity CSV > ValueError
- Educational disclaimer included

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- First subcommand-pattern CLI in the codebase (HEDG-04)
- Four subcommands: status, suggest-roll, log-roll, history
- All subcommands support --output json for programmatic use
- DTE color coding (red/yellow/green) with [ROLL]/[EXPIRING] text markers
- Summary row shows total hedge cost, value, P&L, position count
- Shared parent parser pattern for --output and --config inheritance
- Educational disclaimer on all human output
- ScenarioInput: market drop, holding days, daily volatility with validation
- SQQQResult: simulation output with zero floor enforcement
- PutResult: put payoff with IV expansion tracking
- ComparisonRow: side-by-side SQQQ vs put per scenario
- ComparisonOutput: full comparison with breakevens and disclaimers
- Updated src/models/__init__.py with all 5 model exports
Tasks completed: 1/1
- Create hedge_sizer_cli.py with flat argparse and formatted output

SUMMARY: .planning/phases/08-rolling-tracker-hedge-sizer/08-04-SUMMARY.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
… and put pricing

- Day-by-day SQQQ compounding with -3x leverage and expense ratio
- Three scenario paths: gradual, crash-then-flat, volatile (seeded RNG)
- IV expansion via VIX-SPX regression table from historical crash data
- Breakeven analysis using scipy brentq for SQQQ, analytical for puts
- Path-dependent disclaimers and parameter snapshot in output
- Reuses existing OptionsCalculator for Black-Scholes put pricing
- Add test_expiring_position_generates_suggestion with mocked scan_chain
- Add CLI integration tests: test_cli_help and test_cli_status_json
- Total: 38 tests (36 existing + 2 new)
Tasks completed: 2/2
- Create hedge comparison Pydantic models
- Create HedgeComparisonCalculator (Layer 2)

SUMMARY: .planning/phases/09-sqqq-vs-puts-comparison/09-01-SUMMARY.md
- Add test_cli_help: verifies --help exits 0 with --portfolio flag
- Add test_cli_sizing_skip_budget: verifies sizing with --skip-budget
- Add test_cli_json_output: verifies JSON output with expected keys
- Total: 46 tests (43 existing + 3 new)
Tasks completed: 2/2
- Review and augment RollingTracker tests (36 -> 38)
- Review and augment HedgeSizer tests (43 -> 46)

SUMMARY: .planning/phases/08-rolling-tracker-hedge-sizer/08-06-SUMMARY.md
- argparse CLI with --scenarios, --output, --spot, --strike, --premium flags
- Human-readable comparison table with SQQQ return, drag, put PnL, winner
- JSON output via ComparisonOutput.model_dump_json()
- Breakeven analysis section in human output
- Educational disclaimers in both output formats
- argv preprocessor to handle --scenarios -5,-10,-20,-40 dash parsing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- TestSQQQSimulation: constant return, flat fee loss, volatile drag, zero floor, naive-3x divergence, small drop profit
- TestPutPayoff: deep ITM profitable, OTM premium loss, IV expansion scaling
- TestBreakeven: ATM put analytical breakeven, SQQQ small breakeven range
- TestComparisonOutput: scenario count, path-dependent disclaimer, params snapshot, winner logic consistency
- All synthetic data, zero network calls, pytest.approx for floats

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Mermaid flowchart showing all 4 layers: Config, Models, Calculators, CLIs
- Includes Phase 7, 8, 9 components with phase annotations
- Shows shared OptionsCalculator dependency for put pricing
- External data sources: yfinance, VIX-SPX regression table
- Private data: positions.yaml, roll-history.yaml, budget-tracker.yaml
- Output formats: human-readable text and JSON

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 8 verified (6/6 must-haves passed). Updated roadmap,
requirements, and state to reflect completion.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Archive M2 milestone artifacts:
- Create MILESTONES.md with v2.0 entry
- Archive roadmap to milestones/v2.0-ROADMAP.md
- Archive requirements to milestones/v2.0-REQUIREMENTS.md (29/29 satisfied)
- Move audit report to milestones/M2-MILESTONE-AUDIT.md
- Collapse ROADMAP.md M2 phases into summary
- Update PROJECT.md M2 requirements as complete
- Delete REQUIREMENTS.md (fresh for M3)
- Reset STATE.md for next milestone

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
@AojdevStudio AojdevStudio merged commit f75c987 into main Feb 18, 2026
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@AojdevStudio AojdevStudio deleted the gsd/phase-09-sqqq-vs-puts-comparison branch February 18, 2026 16:04
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bs_input = BlackScholesInput(
spot_price=new_spot,
strike=self.put_strike,
time_to_expiry=self.time_to_expiry,
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P1 Badge Account for elapsed holding days when repricing puts

The put leg is repriced with time_to_expiry=self.time_to_expiry even though each scenario includes a holding horizon and the SQQQ leg is simulated over scenario.holding_days; this means a 1-day and 60-day scenario with the same drop keep the same option tenor, overstating time value and put PnL for longer holds. This can materially skew the comparison output and winner selection, so the repricing step should use remaining tenor after the holding period (or intrinsic-only once expired).

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Comment on lines +286 to +287
sqqq_pnl = sqqq_result.final_value - sqqq_result.initial_value
put_pnl = put_result.pnl
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P1 Badge Compare strategies on normalized returns before picking winner

The winner logic compares sqqq_pnl (dollar PnL on the full SQQQ allocation) against put_pnl (per-share option PnL), so the output is driven by unmatched position sizing rather than strategy performance; with defaults this heavily biases results toward the larger-notional leg. The surrounding comment says the comparison should be normalized, but the code does not do that, so the reported winner can be systematically misleading.

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continue

dte = (pos.expiry - today).days
if dte > 7:
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P2 Badge Use config roll_window_days when filtering roll candidates

Roll suggestions are hardcoded to dte > 7 even though RollingTracker is initialized with HedgeConfig and that model exposes roll_window_days; if a user configures a different roll window (for example 14 days), positions in that custom window are silently excluded. This makes the tool ignore configured policy and can delay intended roll alerts.

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