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GitHub Issues for Investment Platform

This file contains all 47 issues to be created. Run the creation script or create manually.

Phase 1: Database Foundation

Issue 1: Database setup - SQLAlchemy + PostgreSQL/SQLite

Labels: enhancement, database, priority-high

Create database/db.py with:

  • SQLAlchemy engine configuration
  • PostgreSQL for production, SQLite for development
  • Session management (get_db, get_db_session)
  • Connection pooling
  • Environment variable configuration (DATABASE_URL)

Acceptance Criteria:

  • Can connect to both PostgreSQL and SQLite
  • Session management works correctly
  • Environment variables properly loaded

Issue 2: User model - profiles, tax jurisdiction, API keys

Labels: enhancement, database, priority-high Depends on: #1

Create database/models/user.py with:

  • id, email, name, hashed_password
  • tax_jurisdiction (AU, US, etc.)
  • timezone (default: Australia/Sydney)
  • api_key for programmatic access
  • is_active, is_verified flags
  • created_at, updated_at timestamps

Acceptance Criteria:

  • Can create, read, update, delete users
  • Tax jurisdiction defaults to AU

Issue 3: Portfolio model - live, paper, backtest types

Labels: enhancement, database, priority-high Depends on: #1, #2

Create database/models/portfolio.py with:

  • PortfolioType enum (live, paper, backtest)
  • BrokerType enum (alpaca, ibkr, paper)
  • initial_capital, current_cash, currency
  • strategy_name, strategy_config (JSON)
  • CGT tracking fields
  • Relationship to User

Acceptance Criteria:

  • Can create multiple portfolios per user
  • Supports all three portfolio types

Issue 4: Settings model - risk profiles, alert preferences

Labels: enhancement, database, priority-high Depends on: #1, #2

Create database/models/settings.py with:

  • RiskProfile enum (conservative, moderate, aggressive)
  • max_position_pct, max_daily_loss_pct, default_stop_loss_pct
  • position_sizing_method (fixed_fractional, kelly, risk_parity)
  • Alert preferences (email, slack, sms with contact info)
  • Trading hours
  • LLM preferences

Acceptance Criteria:

  • One-to-one relationship with User
  • All risk parameters have sensible defaults

Issue 5: Trade model - execution history with CGT tracking

Labels: enhancement, database, priority-high Depends on: #1, #3

Create database/models/trade.py with:

  • symbol, side (buy/sell), quantity, price, total_value
  • order_type, status (pending, filled, cancelled)
  • signal_source, signal_confidence
  • CGT fields: acquisition_date, cost_basis_per_unit, cost_basis_total
  • holding_period_days, cgt_discount_eligible (>12 months)
  • cgt_gross_gain, cgt_gross_loss, cgt_net_gain
  • tax_year (Australian FY July-June)
  • fx_rate_to_aud for foreign assets

Acceptance Criteria:

  • Full CGT calculation support
  • Tax year correctly calculated (July-June)
  • 50% discount eligibility tracked

Issue 6: Alembic migrations setup

Labels: enhancement, database, priority-high Depends on: #1-5

Setup Alembic for database migrations:

  • Initialize Alembic configuration
  • Create initial migration for all models
  • Add upgrade/downgrade scripts
  • Document migration workflow in README

Acceptance Criteria:

  • Can run migrations up and down
  • Initial migration creates all tables

Phase 2: Data Layer

Issue 7: FRED API integration - interest rates, M2, GDP, CPI

Labels: enhancement, data, priority-high

Create spektiv/dataflows/fred.py with:

  • FRED API client (fredapi package)
  • Series: DFF (Fed Funds), DGS10 (10Y Treasury), M2SL (M2), GDP, CPIAUCSL
  • VIX from CBOE
  • Date range filtering
  • Error handling and retries

Acceptance Criteria:

  • Can fetch all specified series
  • Proper date formatting
  • Rate limit handling

Issue 8: Multi-timeframe aggregation - weekly/monthly OHLCV

Labels: enhancement, data, priority-high

Create spektiv/dataflows/multi_timeframe.py with:

  • Aggregate daily OHLCV to weekly
  • Aggregate daily OHLCV to monthly
  • Preserve volume correctly
  • Handle partial periods

Acceptance Criteria:

  • Weekly aggregation (Mon-Fri)
  • Monthly aggregation
  • Works with yfinance data

Issue 9: Benchmark data - SPY, sector ETFs

Labels: enhancement, data, priority-high

Create spektiv/dataflows/benchmark.py with:

  • SPY for broad market
  • Sector ETFs (XLF, XLK, XLE, XLV, etc.)
  • Relative strength calculation
  • Correlation calculation

Acceptance Criteria:

  • Can calculate relative strength vs SPY
  • Can calculate rolling correlations

Issue 10: Interface routing - add new data vendors

Labels: enhancement, data, priority-high Depends on: #7-9

Update spektiv/dataflows/interface.py:

  • Add FRED to VENDOR_METHODS
  • Add multi_timeframe routing
  • Add benchmark routing
  • Update TOOLS_CATEGORIES

Acceptance Criteria:

  • New vendors accessible via route_to_vendor
  • Fallback chains work correctly

Issue 11: Data caching layer - FRED rate limits

Labels: enhancement, data, priority-medium Depends on: #7

Add caching for FRED data:

  • File-based cache for FRED responses
  • Cache invalidation strategy (daily for most series)
  • Memory cache for frequently accessed data

Acceptance Criteria:

  • Reduces API calls
  • Cache respects rate limits

Phase 3: New Analysts

Issue 12: Momentum Analyst - multi-TF momentum, ROC, ADX

Labels: enhancement, agents, priority-high Depends on: #8

Create spektiv/agents/analysts/momentum_analyst.py with:

  • Multi-timeframe momentum (daily, weekly, monthly)
  • Rate of Change (ROC) calculation
  • ADX (Average Directional Index)
  • Relative strength vs benchmark
  • Volume-weighted momentum

Acceptance Criteria:

  • Produces structured report like other analysts
  • Integrates with debate workflow

Issue 13: Macro Analyst - FRED interpretation, regime detection

Labels: enhancement, agents, priority-high Depends on: #7

Create spektiv/agents/analysts/macro_analyst.py with:

  • Interpret FRED data for market regime
  • Interest rate environment (rising/falling/stable)
  • Inflation/deflation signals
  • Risk-on/risk-off assessment
  • Economic cycle positioning

Acceptance Criteria:

  • Produces structured macro report
  • Identifies current market regime

Issue 14: Correlation Analyst - cross-asset, sector rotation

Labels: enhancement, agents, priority-high Depends on: #9

Create spektiv/agents/analysts/correlation_analyst.py with:

  • Cross-asset correlation analysis
  • Sector rotation signals
  • Safe haven flows (gold, bonds)
  • Currency correlations (if applicable)
  • Divergence detection

Acceptance Criteria:

  • Produces correlation report
  • Identifies unusual correlations

Issue 15: Position Sizing Manager - Kelly, risk parity, ATR

Labels: enhancement, agents, priority-high

Create spektiv/agents/managers/position_sizing_manager.py with:

  • Kelly criterion calculation
  • Risk parity sizing
  • Fixed fractional sizing
  • ATR-based sizing
  • Maximum position limits

Acceptance Criteria:

  • Given signal and confidence, outputs position size
  • Respects risk limits from settings

Issue 16: Analyst integration - add to graph/setup.py workflow

Labels: enhancement, agents, priority-high Depends on: #12-15

Update spektiv/graph/setup.py:

  • Add new analysts to analyst team
  • Update debate workflow to include new insights
  • Ensure position sizing manager is called

Acceptance Criteria:

  • All new analysts contribute to analysis
  • Backward compatible with existing workflow

Phase 4: Memory System

Issue 17: Layered memory - recency, relevancy, importance scoring

Labels: enhancement, memory, priority-medium Depends on: #5

Create spektiv/memory/layered_memory.py with:

  • Recency scoring (exponential decay)
  • Relevancy scoring (similarity to current situation)
  • Importance scoring (based on P&L impact)
  • Memory retrieval with composite score

Acceptance Criteria:

  • FinMem pattern implemented
  • Can retrieve top-k relevant memories

Issue 18: Trade history memory - outcomes, agent reasoning

Labels: enhancement, memory, priority-medium Depends on: #5, #17

Create spektiv/memory/trade_history.py with:

  • Store trade outcomes with full context
  • Link to agent reasoning at time of trade
  • Track what worked vs what didn't
  • Pattern recognition for similar setups

Acceptance Criteria:

  • Full trade context preserved
  • Can query by symbol, timeframe, outcome

Issue 19: Risk profiles memory - user preferences over time

Labels: enhancement, memory, priority-medium Depends on: #4, #17

Create spektiv/memory/risk_profiles.py with:

  • User risk preferences over time
  • Portfolio behavior patterns
  • Drawdown tolerance history
  • Position sizing history

Acceptance Criteria:

  • Tracks risk behavior evolution
  • Informs position sizing

Issue 20: Memory integration - retrieval in agent prompts

Labels: enhancement, memory, priority-medium Depends on: #17-19

Integrate memory into agents:

  • Add memory retrieval to analyst prompts
  • Include relevant past trades in context
  • Update trader agent with memory

Acceptance Criteria:

  • Agents reference relevant past trades
  • Memory influences recommendations

Phase 5: Execution Layer

Issue 21: Broker base interface - abstract broker class

Labels: enhancement, execution, priority-high

Create execution/brokers/base.py with:

  • Abstract Broker class
  • Methods: connect, disconnect, submit_order, cancel_order
  • Methods: get_positions, get_account, get_order_status
  • Error handling patterns

Acceptance Criteria:

  • Clear interface contract
  • All brokers implement same interface

Issue 22: Broker router - route by asset class

Labels: enhancement, execution, priority-high Depends on: #21

Create execution/brokers/broker_router.py with:

  • Route by exchange (NYSE, NASDAQ -> Alpaca)
  • Route by asset type (futures -> IBKR)
  • Route by symbol suffix (.AX -> IBKR)
  • Fallback handling

Acceptance Criteria:

  • Correct routing for all asset classes
  • Clear routing rules

Issue 23: Alpaca broker - US stocks, ETFs, crypto

Labels: enhancement, execution, priority-high Depends on: #21, #22

Create execution/brokers/alpaca_broker.py with:

  • Alpaca API integration (alpaca-py)
  • Paper and live modes
  • US stocks, ETFs
  • Crypto trading
  • Order submission and tracking

Acceptance Criteria:

  • Can place orders via Alpaca API
  • Supports paper trading mode

Issue 24: IBKR broker - futures, ASX equities

Labels: enhancement, execution, priority-high Depends on: #21, #22

Create execution/brokers/ibkr_broker.py with:

  • Interactive Brokers API (ib_insync)
  • Futures contracts (GC, SI, ES)
  • Australian equities (ASX)
  • Order submission and tracking

Acceptance Criteria:

  • Can place orders via IBKR
  • Supports futures and ASX

Issue 25: Paper broker - simulation mode

Labels: enhancement, execution, priority-high Depends on: #21, #22

Create execution/brokers/paper_broker.py with:

  • Simulated order execution
  • Realistic fill simulation
  • Position tracking
  • P&L calculation
  • No real money at risk

Acceptance Criteria:

  • Full trading simulation
  • Tracks positions and P&L

Issue 26: Order types and manager - market, limit, stop, trailing

Labels: enhancement, execution, priority-high Depends on: #21

Create execution/orders/:

  • order_types.py - Order, OrderType, OrderStatus enums
  • order_manager.py - Order lifecycle management
  • Support: market, limit, stop, stop_limit, trailing_stop

Acceptance Criteria:

  • All order types supported
  • Order state machine correct

Issue 27: Risk controls - position limits, loss limits

Labels: enhancement, execution, priority-high Depends on: #4

Create execution/risk_controls/:

  • position_limits.py - Max position size, concentration
  • loss_limits.py - Daily loss limit, drawdown limit
  • Pre-trade validation

Acceptance Criteria:

  • Orders rejected if limits exceeded
  • Clear rejection messages

Phase 6: Portfolio Management

Issue 28: Portfolio state - holdings, cash, mark-to-market

Labels: enhancement, portfolio, priority-high Depends on: #3, #5

Create portfolio/portfolio_state.py with:

  • Current holdings
  • Cash balance
  • Total portfolio value (mark-to-market)
  • Real-time pricing

Acceptance Criteria:

  • Accurate portfolio valuation
  • Handles multiple currencies

Issue 29: Position tracker - open/closed, cost basis, tax lots

Labels: enhancement, portfolio, priority-high Depends on: #5, #28

Create portfolio/position_tracker.py with:

  • Open positions with cost basis
  • Closed positions with realized P&L
  • Tax lot tracking (FIFO, LIFO, specific ID)
  • Average cost calculation

Acceptance Criteria:

  • Correct cost basis tracking
  • Tax lot matching works

Issue 30: Performance metrics - Sharpe, drawdown, returns

Labels: enhancement, portfolio, priority-high Depends on: #28, #29

Create portfolio/performance.py with:

  • Daily, monthly, yearly returns
  • Sharpe ratio
  • Maximum drawdown
  • Win rate, profit factor
  • Benchmark comparison

Acceptance Criteria:

  • Industry-standard calculations
  • Matches known benchmarks

Issue 31: Australian CGT calculator - 50% discount, tax reports

Labels: enhancement, portfolio, priority-high Depends on: #5, #29

Create portfolio/tax_calculator.py with:

  • Australian CGT calculations
  • 50% discount for assets held >12 months
  • Tax year reports (July-June)
  • Currency conversion for foreign assets
  • Capital loss tracking

Acceptance Criteria:

  • Correct CGT calculations
  • Tax year correctly determined
  • Report format suitable for tax return

Phase 7: Simulation & Strategy

Issue 32: Scenario runner - parallel portfolio simulations

Labels: enhancement, simulation, priority-high Depends on: #25, #28

Create simulation/scenario_runner.py with:

  • Run multiple portfolios in parallel
  • Same market data, different strategies
  • Paper trading infrastructure
  • Result collection

Acceptance Criteria:

  • Can run 5+ parallel simulations
  • Results properly isolated

Issue 33: Strategy comparator - performance comparison, stats

Labels: enhancement, simulation, priority-high Depends on: #30, #32

Create simulation/strategy_comparator.py with:

  • Compare performance across scenarios
  • Statistical significance testing
  • Risk-adjusted return comparison
  • Ranking and scoring

Acceptance Criteria:

  • Clear comparison output
  • Statistical confidence levels

Issue 34: Economic conditions - regime tagging, evaluation

Labels: enhancement, simulation, priority-high Depends on: #7, #32

Create simulation/economic_conditions.py with:

  • Tag scenarios by economic regime
  • Bull/bear/sideways market detection
  • Evaluate strategy performance by condition
  • Regime-specific recommendations

Acceptance Criteria:

  • Correct regime identification
  • Performance breakdown by regime

Issue 35: Signal to order converter

Labels: enhancement, strategy, priority-high Depends on: #26

Create strategy/signal_to_order.py with:

  • Convert BUY/SELL signals to orders
  • Apply position sizing
  • Set stop loss and take profit
  • Order validation

Acceptance Criteria:

  • Signals converted to valid orders
  • Risk parameters applied

Issue 36: Strategy executor - end-to-end orchestration

Labels: enhancement, strategy, priority-high Depends on: #32-35

Create strategy/strategy_executor.py with:

  • End-to-end orchestration
  • Signal generation -> Order -> Execution
  • Error handling and retries
  • Logging and monitoring

Acceptance Criteria:

  • Full trade lifecycle managed
  • Robust error handling

Phase 8: Alerts

Issue 37: Alert manager - orchestration and routing

Labels: enhancement, alerts, priority-medium Depends on: #4

Create alerts/alert_manager.py with:

  • Alert orchestration
  • Route to appropriate channels
  • Priority levels (info, warning, critical)
  • Throttling to prevent spam

Acceptance Criteria:

  • Alerts routed correctly
  • Critical alerts always delivered

Issue 38: Email channel - SMTP/SendGrid

Labels: enhancement, alerts, priority-medium Depends on: #37

Create alerts/channels/email_channel.py with:

  • SMTP support
  • SendGrid API support
  • HTML email templates
  • Delivery confirmation

Acceptance Criteria:

  • Emails delivered reliably
  • Professional formatting

Issue 39: Slack channel - webhooks

Labels: enhancement, alerts, priority-medium Depends on: #37

Create alerts/channels/slack_channel.py with:

  • Slack webhook integration
  • Rich message formatting
  • Channel routing

Acceptance Criteria:

  • Messages appear in Slack
  • Formatting correct

Issue 40: SMS channel - Twilio

Labels: enhancement, alerts, priority-medium Depends on: #37

Create alerts/channels/sms_channel.py with:

  • Twilio API integration
  • SMS formatting
  • Delivery status tracking

Acceptance Criteria:

  • SMS delivered
  • Critical alerts work

Phase 9: Backtest

Issue 41: Backtest engine - historical replay, slippage

Labels: enhancement, backtest, priority-medium Depends on: #25, #28

Create backtest/backtest_engine.py with:

  • Historical data replay
  • Slippage modeling
  • Commission modeling
  • Position sizing simulation

Acceptance Criteria:

  • Realistic backtesting
  • Configurable slippage/commission

Issue 42: Results analyzer - metrics, trade analysis

Labels: enhancement, backtest, priority-medium Depends on: #30, #41

Create backtest/results_analyzer.py with:

  • Performance metrics
  • Trade-by-trade analysis
  • Equity curve
  • Drawdown analysis

Acceptance Criteria:

  • Comprehensive analysis
  • Visual outputs

Issue 43: Report generator - PDF/HTML reports

Labels: enhancement, backtest, priority-low Depends on: #42

Create backtest/report_generator.py with:

  • PDF report generation
  • HTML report generation
  • Charts and graphs
  • Summary statistics

Acceptance Criteria:

  • Professional reports
  • Exportable

Phase 10: API & Docs

Issue 44: FastAPI application setup

Labels: enhancement, api, priority-low Depends on: #1-6

Create api/app.py with:

  • FastAPI application
  • CORS configuration
  • Error handling
  • Health check endpoint

Acceptance Criteria:

  • API starts and responds
  • Health check works

Issue 45: API routes - users, portfolios, trades, signals

Labels: enhancement, api, priority-low Depends on: #44

Create api/routes/:

  • users.py - User CRUD
  • portfolios.py - Portfolio CRUD
  • trades.py - Trade history
  • signals.py - Signal retrieval

Acceptance Criteria:

  • All CRUD operations work
  • Proper error responses

Issue 46: API authentication - JWT

Labels: enhancement, api, priority-low Depends on: #44, #45

Add JWT authentication:

  • Login endpoint
  • Token generation
  • Token validation middleware
  • Refresh tokens

Acceptance Criteria:

  • Secure authentication
  • Token refresh works

Issue 47: Documentation - user guide, developer docs

Labels: documentation, priority-low

Create documentation:

  • User guide (how to use)
  • Developer guide (how to extend)
  • API documentation (OpenAPI)
  • Architecture overview

Acceptance Criteria:

  • Clear documentation
  • Getting started guide