fix bruno collection
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# PHASES.md
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Complete roadmap for market-screener evolution from Phase 9 through Phase 16+.
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## Phase 9 — Subdomain Restructure: Server Layer Organization
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**Goal:** Reorganize `server/` from flat layer-based structure to domain-driven structure.
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**Timeline:** 3 weeks.
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### 9a — Create shared infrastructure layer
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Create `server/domains/shared/` hierarchy:
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```
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server/domains/shared/
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├── entities/ (models + their types together)
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│ ├── Asset.ts
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│ ├── Stock.ts
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│ ├── Etf.ts
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│ ├── Bond.ts
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│ └── index.ts
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├── adapters/ (external API wrappers, renamed from "clients")
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│ ├── YahooFinanceAdapter.ts
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│ ├── AnthropicAdapter.ts
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│ ├── SimpleFINAdapter.ts
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│ └── index.ts
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├── services/ (cross-domain services)
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│ ├── BenchmarkProvider.ts
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│ ├── CatalystAnalyst.ts
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│ ├── LLMAnalyst.ts
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│ └── index.ts
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├── scoring/ (rules + regime management)
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│ ├── ScoringConfig.ts
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│ ├── GateValidator.ts
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│ ├── MarketRegime.ts
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│ └── index.ts
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├── persistence/ (SQLite stores)
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│ ├── MarketCallStore.ts
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│ ├── PortfolioStore.ts
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│ └── index.ts
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├── types/ (all domain types)
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│ ├── asset.model.ts
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│ ├── finance.model.ts
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│ ├── market.model.ts
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│ ├── [...other models]
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│ └── index.ts
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├── config/
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│ └── constants.ts
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├── utils/
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│ ├── logger.ts
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│ ├── Chunker.ts
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│ └── index.ts
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├── db/
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│ └── index.ts
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├── schemas.ts
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└── index.ts
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```
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### 9b — Extract screener domain
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```
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server/domains/screener/
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├── ScreenerController.ts
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├── ScreenerEngine.ts
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├── PersonalFinanceAnalyzer.ts
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├── scorers/
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│ ├── StockScorer.ts
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│ ├── EtfScorer.ts
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│ ├── BondScorer.ts
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│ └── index.ts
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├── transform/
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│ ├── DataMapper.ts
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│ ├── RuleMerger.ts
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│ └── index.ts
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└── index.ts
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```
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### 9c — Extract portfolio domain
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```
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server/domains/portfolio/
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├── PortfolioController.ts
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├── PortfolioAdvisor.ts
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├── persistence/
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│ └── PortfolioStore.ts
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└── index.ts
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```
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### 9d — Extract calls domain
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```
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server/domains/calls/
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├── CallsController.ts
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├── CalendarService.ts
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├── persistence/
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│ └── MarketCallStore.ts
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└── index.ts
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```
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### 9e — Extract finance domain
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```
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server/domains/finance/
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├── FinanceController.ts
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└── index.ts
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```
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### 9f — Clean up old directories
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Remove: `server/controllers/`, `server/services/`, `server/repositories/`, `server/clients/`, `server/models/`, `server/scorers/`, `server/config/`, `server/types/`, `server/utils/`
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### 9g — Update documentation in CLAUDE.md
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Update "Server layer map" section with new domain structure.
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### 9h — Smoke test all routes
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Create integration smoke test verifying all major routes work after restructure.
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---
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## Phase 10 — UI Component Restructure & Clarity
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**Goal:** Mirror Phase 9 server restructure at UI layer. Organize components by domain.
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**Timeline:** 1 week.
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### 10a — Create component hierarchy
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```
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ui/src/lib/components/
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├── shared/
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│ ├── Spinner.svelte
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│ ├── VerdictPill.svelte
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│ ├── SignalBadge.svelte
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│ └── index.ts
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├── screener/
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│ ├── AssetTable.svelte
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│ ├── AnalysisSidebar.svelte
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│ └── index.ts
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├── portfolio/
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│ ├── AddHoldingForm.svelte
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│ ├── AdviceTable.svelte
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│ └── index.ts
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└── calls/
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├── CallForm.svelte
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├── CallCard.svelte
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└── index.ts
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```
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### 10b — Split utils and types
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```
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lib/utils/
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├── formatting.ts
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├── sorting.ts
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├── verdicts.ts
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└── index.ts
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lib/types/
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├── ui.types.ts
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├── portfolio.types.ts
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└── index.ts
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```
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### 10c — Update all imports in routes + stores
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### 10d — Extract reusable layout components
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### 10e — UI Phase 10 complete
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---
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## Phase 10.5 — Professional-Grade Screener UI (Institutional Research Tool)
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**Goal:** Build professional screener interface showing complete investment research capabilities.
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**Timeline:** 4-6 weeks (after Phase 10).
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### 10.5a — Three-Layer Layout
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```
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Sidebar (280px) | Main Table (flex) | Tearsheet Panel (420px)
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────────────────┼──────────────────┼──────────────────────
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Advanced │ Compact table │ Forensic detail
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filters │ 10 columns only │ Full metrics
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(left) │ │ Peer comparison
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│ Scannable │ Decision framework
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Quick presets │ minimal │ Risk breakdown
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│ │ (right side-panel)
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```
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### 10.5b — Sidebar: Advanced Filtering
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- Preset buttons: All, Strong Buy, Buy, Hold, Avoid
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- Custom filters: P/E Range, ROE Min, Dip %, D/E Max
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- Quick presets: "Value Trap Screen", "Growth at Fair Price", "Dip Opportunity"
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### 10.5c — Main Table: Minimal, Scannable
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10 columns: Ticker | Price | Verdict | Score | P/E | ROE | 52W | DCF | Flags | Menu
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- Sortable, sticky header
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- Monospace numbers (professional)
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- Color-coded metrics
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- Click row → opens tearsheet
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### 10.5d — Tearsheet Panel: Professional Research
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Right-side slide-in (420px) with sections:
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1. Core Metrics (4-grid, color-coded cards)
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2. Valuation Context (comparison table)
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3. Decision Framework (gate-by-gate breakdown)
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4. Risk Breakdown (ranked, quantified)
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5. Threshold Sensitivity (what-if scenarios)
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6. Peer Comparison
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7. CTA Row (Add to Watchlist, Decision Log)
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### 10.5e — Decision Logging & Backtest
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- Save thesis + entry date/price
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- Track 30/60/90 day outcomes
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- Simple review modal ("did thesis play out?")
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- Backtest dashboard (win rate by signal type)
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### 10.5f — Implementation (Phased)
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- Week 1-2: Core UI (sidebar, table, tearsheet basic)
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- Week 2-3: Tearsheet sections (all 7 sections)
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- Week 3-4: Interactivity (sorting, filters, animation)
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- Week 4-5: Decision logging
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- Week 5-6: Backtest dashboard (optional)
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---
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## Phase 10.6 — Portfolio Integration: Market Analysis → Action
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**Goal:** Connect screener signals + market context to portfolio decisions.
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### 10.6a — Market-Aware Position Sizing
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Auto-calculate recommended position size based on:
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- Stock verdict
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- Market regime
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- Sector momentum
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- Portfolio allocation
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Display: "Recommended: 2-4% of portfolio" or "$2,000-$4,000"
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### 10.6b — Portfolio Dashboard: Integrated View
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Single screen showing:
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1. Holdings + P&L
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2. Allocation vs Target
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3. Market Context
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4. Screener Signals
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5. Recommended Action
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### 10.6c — Screener-Portfolio Bridge
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Add "Your Holdings" column in screener showing:
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- "You own 2% | +$1,000 gain"
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- Verdict changes
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- Thesis change alerts
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### 10.6d — Thesis Journal (Simplified)
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When adding position:
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1. Why I'm buying (pick ONE reason)
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2. What I'll watch (pick 1-2 metrics)
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3. Review date (auto 30 days)
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### 10.6e — Rebalancing Advisor
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Monitor allocation vs target. When screener verdict changes on existing holding, suggest action.
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---
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## Phase 10.7 — Newbie UX: Progressive Disclosure
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**Goal:** Professional tool with newbie-friendly interface. Same power, different experience.
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### 10.7a — Screener Entry: Strategy-Based
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Instead of filters, ask: "What are you looking for?"
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Options:
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- ○ Solid companies at good prices (Balanced)
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- ○ Hot stocks with momentum (Momentum)
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- ○ Beaten-down bargains (Value)
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- ○ Let me customize filters (Advanced)
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### 10.7b — Table View: Plain Language Explanations
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Minimal table: Ticker | Price | Verdict | Why? ℹ️
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Clicking "ℹ️" shows plain-language explanation with reasons, scores, and what it means.
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### 10.7c — Buy Decision Helper
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Calculate recommended position size automatically. Show:
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- Star rating (intuitive)
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- Concrete dollars (not abstract %)
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- Clear "safe" path highlighted
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### 10.7d — Portfolio Status View (Not Analysis)
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Show status + guidance, not complex metrics:
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- Visual breakdown (bars)
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- What it means
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- Concrete actions (sell, buy, do nothing)
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### 10.7e — Market Context: Status Light + Impact
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Use traffic light system:
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- 🟢 Good / ⚠️ Mixed / 🔴 Bad
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- Plain explanation of why
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- Impact on YOUR portfolio
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### 10.7f — Thesis Logging: Simple Checklist
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Pick ONE reason + 1-2 metrics to watch. Built-in review schedule.
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### 10.7g — After Buying: 30-Day Check-In
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Auto-reminder after 30 days showing:
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- How metrics moved vs prediction
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- Thesis status (working / shaken / broken)
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- Next action
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### 10.7h — Newbie Mode vs Pro Mode (Toggle)
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**Newbie Mode:** Simplified screener, plain language, auto position sizing, status lights, guided workflows
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**Pro Mode:** Full filter control, all metrics, raw data, advanced analysis, complete transparency
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---
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## Phase 10.8 — Earnings Calendar: Context, Not Destination
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**Goal:** Integrate earnings data contextually, NOT as standalone tab.
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### 10.8a — Earnings in Screener Tearsheet (Primary)
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```
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UPCOMING EVENTS:
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├── Earnings: July 30, 2026 (18 days away)
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│ ├── EPS estimate: $6.50
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│ ├── Historical beat rate: 65%
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│ ├── Avg price move on earnings: +3% (beat), -2% (miss)
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│ └── Timing decision: "Buy now before earnings?" or "Wait?"
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│
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├── Ex-dividend: June 15 (6 days away)
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│ └── Dividend: $0.24/share
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│
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└── Analyst call: Post-earnings July 30
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```
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### 10.8b — Earnings in Portfolio (Secondary)
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Portfolio holdings view shows upcoming events for YOUR positions with thesis-specific tracking.
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### 10.8c — Earnings Discovery Widget (Optional, Tertiary)
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Light calendar feature in screener header (NOT main nav):
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```
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📅 25 earnings this week in your screened results
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└── [View by day] [View by verdict]
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```
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### 10.8d — What NOT to Build
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❌ **Standalone "Calendar" nav tab** — creates bloat, out-of-context data, redundant.
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### 10.8e — Earnings in Thesis Journal
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Earnings become key tracking metric when user logs thesis.
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### 10.8f — Design Note: Revisit Earnings Display Format
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**⚠️ DESIGN REVIEW NEEDED:**
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Consider consistency across three locations, visual hierarchy differences, and mobile responsiveness before finalizing visual design.
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---
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## Phase 10.9 — Strong Buys: Professional Dip Opportunity Monitor
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**Goal:** Flag quality stocks when they drop 5%+ from 52W high, with market analysis of why.
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### 10.9a — Data Structure
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| Field | Source | Purpose |
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|-------|--------|---------|
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| Ticker | Yahoo Finance | Stock identifier |
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| Current Price | Yahoo Finance daily fetch | Entry price today |
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| 52W High | Yahoo Finance | Reference for dip % |
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| Dip % | Calculated | Triggers display if ≥5% |
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| Screener Verdict | ScreenerEngine | Quality ranking |
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| Dip Reason | Market Analysis | Macro vs company issue |
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| Market Context | Daily fetched | Why dropped? Temporary? |
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| Your Play | LLM analysis | Buy dip or wait? |
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| Recommended Action | Position sizing | "Add 2-4% to portfolio" |
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### 10.9b — Fetching Mechanism (Daily)
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1. Get "Too Big to Fail" universe (~150 stocks: mega-cap + large-cap + watchlist)
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2. Fetch prices + 52W high (one Yahoo batch call)
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3. Filter dips ≥5% from 52W high
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4. Run screener on dipped stocks
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5. Analyze why dipped (macro vs company)
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6. Combine + cache (TTL 24 hours)
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7. API serves from cache
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### 10.9c — UI: Tabular Display of Dip Opportunities
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| Ticker | Price | Dip % | Verdict | Why It Dipped | Your Play | Action |
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|--------|-------|-------|---------|---------------|-----------|--------|
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| AAPL | $189.50 | -9.76% | Strong Buy (8.2) | Fed rates high (macro, not company) | Buy dip. iPhone intact. | [+2-4%] |
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| JPM | $215.30 | -7.2% | Strong Buy (7.8) | Sector rotation (capital away) | Defensive play. Undervalued. | [+3%] |
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- Sortable by: Dip %, Verdict, Your Play
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- Click row → full tearsheet
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- Daily refresh
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- Threshold configurable: 5% (default) → 10% → 15%
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### 10.9d — Configuration (User Control)
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```
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Settings > Strong Buys Monitor:
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Stock Universe:
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☑ Mega-cap (10)
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☑ Large-cap (50)
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☑ My Watchlist (custom)
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Dip Threshold:
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○ 5% (Aggressive)
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○ 10% (Balanced)
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○ 15% (Conservative)
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Update Frequency:
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○ Daily morning (9:30 AM)
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● Daily EOD (4:00 PM)
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```
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### 10.9e — Design Note: Revisit Tabular Format
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**⚠️ DESIGN REVIEW NEEDED:**
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Consider:
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1. **Card-based alternative** (cleaner, easier scan) vs current **compact table**
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2. **Hybrid approach** (desktop table + mobile cards)
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Recommendation: Implement Phase 10.9a, gather user feedback, adjust design.
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---
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## Phase 10.5j — Comprehensive Free Data Stack (Zero Cost, Zero Redundancy)
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**Philosophy:** Professional-grade screener using only FREE sources. No $99-$200/mo subscriptions. Each source has ONE clear job (no duplication).
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### Data Sources
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| Source | Cost | Job | Why |
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|--------|------|-----|-----|
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| Yahoo Finance (YahooFinanceClient) | $0 | Core metrics (P/E, ROE, FCF, D/E, analyst ratings) | Already integrated. No alternatives needed. |
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| yfinance | $0 | Per-ticker enrichment (news, earnings dates, dividends) | Wraps Yahoo, optimized for news extraction. |
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| Finnhub FREE | $0 | Earnings calendar + estimates only | Reliable future events (3-month lookahead). |
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| Alpha Vantage FREE | $0 | Market context + sentiment (macro-focused) | Sector trends, Fed decisions, keyword search. |
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| API Ninjas FREE | $0 | Earnings backup only (redundancy layer) | Fallback if Finnhub hits rate limits. |
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| Your LLM (Claude) | ~$50/mo | Intelligence layer (turns data into insights) | Sentiment analysis, decision framework, thesis validation. |
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**Total:** ~$50/mo (just LLM), vs $300-400/mo for Bloomberg/FactSet.
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### Data Flow in Tearsheet
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1. User screens stocks → ScreenerEngine uses YahooFinanceClient
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2. Metrics cached in memory/state (no extra calls)
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3. User clicks row → Tearsheet opens
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4. Fetch per-ticker enrichment on-demand (yfinance, Finnhub, Alpha Vantage — parallel)
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5. Process with LLM (if enabled) for sentiment + decision framework
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6. Display complete tearsheet
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### Integration Timeline
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- **Week 1:** Add yfinance news enrichment
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- **Week 2:** Add Finnhub earnings calendar
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- **Week 3:** Add Alpha Vantage market context
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- **Week 4:** Add API Ninjas as backup
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- **Week 5:** Wire everything into tearsheet
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- **Week 6:** Add LLM enrichment (optional)
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### Why This Approach
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✅ **Zero Cost:** $0/month (all sources FREE)
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✅ **Zero Redundancy:** Each source has ONE job, no overlap
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||||
✅ **Professional Grade:** Layered sources like institutional traders use
|
||||
✅ **Reliability:** Redundancy where it matters (earnings calendar via Finnhub + API Ninjas backup)
|
||||
✅ **Intelligent:** Your LLM adds 10x value without additional data cost
|
||||
|
||||
### Rate Limits & Sustainability
|
||||
|
||||
- Yahoo Finance: No official limits (proven in production)
|
||||
- yfinance: No limits (wraps Yahoo)
|
||||
- Finnhub FREE: 60 calls/minute (sufficient for 250 stocks)
|
||||
- Alpha Vantage FREE: 5 calls/minute (one daily call, easily manageable)
|
||||
- API Ninjas: 100 calls/month (backup only, minimal usage)
|
||||
|
||||
---
|
||||
|
||||
## Phase 11 — Day Trading: Authentication & Authorization
|
||||
|
||||
**Goal:** Add multi-user support with JWT auth, role-based access control, and portfolio isolation.
|
||||
|
||||
**Timeline:** 2-3 weeks.
|
||||
|
||||
### Why Auth is First
|
||||
|
||||
Can't test multi-user portfolios, public + private access, Discord notifications with user context, or trade journal attribution without auth.
|
||||
|
||||
### 11a — Create auth domain
|
||||
|
||||
```
|
||||
server/domains/auth/
|
||||
├── AuthController.ts
|
||||
├── AuthService.ts
|
||||
├── JWTStrategy.ts
|
||||
├── RBACGuard.ts
|
||||
├── persistence/
|
||||
│ └── UserStore.ts
|
||||
└── types/
|
||||
└── auth.model.ts
|
||||
```
|
||||
|
||||
### 11b — Database schema changes
|
||||
|
||||
```sql
|
||||
CREATE TABLE users (
|
||||
id TEXT PRIMARY KEY,
|
||||
email TEXT UNIQUE NOT NULL,
|
||||
password_hash TEXT NOT NULL,
|
||||
role TEXT DEFAULT 'viewer' CHECK (role IN ('trader', 'viewer', 'admin')),
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
last_login DATETIME
|
||||
);
|
||||
|
||||
ALTER TABLE holdings ADD COLUMN user_id TEXT NOT NULL REFERENCES users(id);
|
||||
ALTER TABLE market_calls ADD COLUMN created_by TEXT REFERENCES users(id);
|
||||
```
|
||||
|
||||
### 11c — Middleware + route protection
|
||||
|
||||
Apply RBACGuard to protected routes. JWT secret from env var.
|
||||
|
||||
### 11d — UI auth layer
|
||||
|
||||
Add `routes/auth/login/` and `routes/auth/register/`.
|
||||
|
||||
Create `lib/stores/auth.store.svelte.ts` for currentUser, JWT, login/logout.
|
||||
|
||||
---
|
||||
|
||||
## Phase 12 — Day Trading: News Webhooks
|
||||
|
||||
**Goal:** Ingest real-time market news via Polygon.io webhooks.
|
||||
|
||||
**Timeline:** 2-3 weeks.
|
||||
|
||||
### Why Webhooks Come Second
|
||||
|
||||
News feeds everything downstream: Safe Buys monitor, LLM analysis, price dips.
|
||||
|
||||
### 12a — Create news domain
|
||||
|
||||
```
|
||||
server/domains/news/
|
||||
├── NewsController.ts
|
||||
├── WebhookHandler.ts
|
||||
├── NewsStore.ts
|
||||
├── NewsQueue.ts (BullMQ worker)
|
||||
├── persistence/
|
||||
│ └── NewsArticleStore.ts
|
||||
└── types/
|
||||
└── news.model.ts
|
||||
```
|
||||
|
||||
### 12b — Database schema
|
||||
|
||||
```sql
|
||||
CREATE TABLE news_articles (
|
||||
id TEXT PRIMARY KEY,
|
||||
ticker TEXT NOT NULL,
|
||||
headline TEXT NOT NULL,
|
||||
body TEXT,
|
||||
source TEXT,
|
||||
url TEXT,
|
||||
sentiment TEXT,
|
||||
published_at DATETIME,
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
|
||||
);
|
||||
|
||||
CREATE INDEX idx_news_ticker_date ON news_articles(ticker, published_at DESC);
|
||||
```
|
||||
|
||||
### 12c — Set up Polygon.io webhook
|
||||
|
||||
1. Subscribe to Polygon news API (~$200/mo)
|
||||
2. Register webhook: `https://yourapp.com/webhooks/news`
|
||||
3. Validate signature (Polygon sends HMAC)
|
||||
4. Queue article for async processing
|
||||
|
||||
### 12d — Async processing with BullMQ
|
||||
|
||||
Queue processes articles:
|
||||
1. Store in DB
|
||||
2. Trigger LLM analysis if key tickers mentioned
|
||||
3. Notify subscribers (Discord, etc)
|
||||
|
||||
---
|
||||
|
||||
## Phase 13 — Day Trading: Prompt Caching & LLM Optimization
|
||||
|
||||
**Goal:** Reduce LLM costs by 90% using Anthropic prompt caching.
|
||||
|
||||
**Timeline:** 2-3 weeks.
|
||||
|
||||
### 13a — Create llm domain
|
||||
|
||||
```
|
||||
server/domains/llm/
|
||||
├── LLMRouter.ts
|
||||
├── PromptCache.ts
|
||||
├── LLMAnalyst.ts (refactored)
|
||||
├── persistence/
|
||||
│ ├── AnalysisStore.ts
|
||||
│ └── CacheStore.ts
|
||||
└── types/
|
||||
└── llm.model.ts
|
||||
```
|
||||
|
||||
### 13b — Database schema
|
||||
|
||||
```sql
|
||||
CREATE TABLE llm_analysis (
|
||||
id TEXT PRIMARY KEY,
|
||||
ticker TEXT NOT NULL,
|
||||
analysis_result TEXT NOT NULL,
|
||||
model_used TEXT DEFAULT 'claude-opus',
|
||||
tokens_used INTEGER,
|
||||
cache_hit BOOLEAN DEFAULT false,
|
||||
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
|
||||
);
|
||||
```
|
||||
|
||||
### 13c — Implement Anthropic prompt caching
|
||||
|
||||
Add `cache_control: { type: 'ephemeral' }` to system prompt message block.
|
||||
|
||||
Use `anthropic-beta: prompt-caching-2024-07-31` header.
|
||||
|
||||
### 13d — LLM Router for cost optimization
|
||||
|
||||
Route to cheaper models (Sonnet) when cost-sensitive. Fallback to OpenAI if rate-limited.
|
||||
|
||||
---
|
||||
|
||||
## Phase 14 — Day Trading: Safe Buys Monitor with Discord Alerts
|
||||
|
||||
**Goal:** Monitor safe-buy stocks in real-time, detect 5%+ dips, notify via Discord.
|
||||
|
||||
**Timeline:** 3-4 weeks.
|
||||
|
||||
### 14a — Create trading domain
|
||||
|
||||
```
|
||||
server/domains/trading/
|
||||
├── TradingController.ts
|
||||
├── DipDetector.ts
|
||||
├── PriceMonitor.ts
|
||||
├── DiscordNotifier.ts
|
||||
├── persistence/
|
||||
│ ├── PriceSnapshotStore.ts
|
||||
│ └── TradeSignalStore.ts
|
||||
└── types/
|
||||
└── trading.model.ts
|
||||
```
|
||||
|
||||
### 14b — Database schema
|
||||
|
||||
```sql
|
||||
CREATE TABLE price_snapshots (
|
||||
id TEXT PRIMARY KEY,
|
||||
ticker TEXT NOT NULL,
|
||||
price REAL NOT NULL,
|
||||
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
source TEXT,
|
||||
dip_detected BOOLEAN DEFAULT false
|
||||
);
|
||||
|
||||
CREATE TABLE trading_signals (
|
||||
id TEXT PRIMARY KEY,
|
||||
ticker TEXT NOT NULL,
|
||||
signal_type TEXT CHECK (signal_type IN ('strong_buy', 'dip', 'warning')),
|
||||
entry_price REAL,
|
||||
detected_at DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
notified BOOLEAN DEFAULT false,
|
||||
outcome TEXT
|
||||
);
|
||||
```
|
||||
|
||||
### 14c — Real-time price polling
|
||||
|
||||
Check watched tickers every 5 seconds. Filter dips ≥5%. Process via DipDetector.
|
||||
|
||||
### 14d — Discord notifications
|
||||
|
||||
Send rich embeds with:
|
||||
- 🔴 5% Dip Detected: TICKER
|
||||
- Price fell from $X to $Y (-%Z)
|
||||
- LLM sentiment + recommendation
|
||||
- Risks
|
||||
|
||||
---
|
||||
|
||||
## Phase 15 — Day Trading: Trade Journal & Performance Tracking
|
||||
|
||||
**Goal:** Log every decision, track outcomes, measure strategy performance.
|
||||
|
||||
**Timeline:** 1-2 weeks.
|
||||
|
||||
### 15a — Database schema
|
||||
|
||||
```sql
|
||||
CREATE TABLE trade_journal (
|
||||
id TEXT PRIMARY KEY,
|
||||
user_id TEXT NOT NULL REFERENCES users(id),
|
||||
ticker TEXT NOT NULL,
|
||||
signal TEXT,
|
||||
entry_price REAL NOT NULL,
|
||||
entry_date DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
exit_price REAL,
|
||||
exit_date DATETIME,
|
||||
outcome TEXT CHECK (outcome IN ('win', 'loss', 'pending')),
|
||||
pnl REAL,
|
||||
reason TEXT,
|
||||
notes TEXT
|
||||
);
|
||||
|
||||
CREATE INDEX idx_journal_user ON trade_journal(user_id, entry_date DESC);
|
||||
```
|
||||
|
||||
### 15b — Trade stats dashboard
|
||||
|
||||
Compute daily aggregates:
|
||||
- Total trades, wins, losses
|
||||
- Win rate, total P&L
|
||||
- Average win/loss, best/worst signal
|
||||
|
||||
### 15c — UI: Trade Stats Dashboard
|
||||
|
||||
Display stats + trade history with filtering.
|
||||
|
||||
---
|
||||
|
||||
## Phase 16 — Multi-LLM Support (Optional)
|
||||
|
||||
**Goal:** Support Claude, OpenAI, optionally Llama for cost optimization.
|
||||
|
||||
**Timeline:** 2-3 weeks (do after Phase 14).
|
||||
|
||||
### Minimal implementation
|
||||
|
||||
```typescript
|
||||
const MODELS = {
|
||||
'claude-opus': { cost: 0.015, speed: 'slow', quality: 'best' },
|
||||
'claude-sonnet': { cost: 0.003, speed: 'fast', quality: 'good' },
|
||||
'gpt-4': { cost: 0.03, speed: 'medium', quality: 'excellent' },
|
||||
};
|
||||
|
||||
async analyze(ticker: string, preferredModel?: string) {
|
||||
const model = preferredModel || 'claude-sonnet';
|
||||
return await routers[model].analyze(ticker);
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Production Readiness Checklist
|
||||
|
||||
**Before going live:**
|
||||
|
||||
- [ ] Environment variables locked down (.env.production, no secrets in code)
|
||||
- [ ] Database: Migrate SQLite → Postgres if expect >10 concurrent users
|
||||
- [ ] Job Queue: Set up BullMQ with Redis
|
||||
- [ ] Logging: Add structured logging (Winston, Pino) to track LLM calls + costs
|
||||
- [ ] Rate Limiting: Enabled on all public endpoints (@fastify/rate-limit)
|
||||
- [ ] Discord Webhook: Test alerts with real market data
|
||||
- [ ] Auth: JWT secret rotated, session timeout 1h
|
||||
- [ ] SSL/TLS: HTTPS enforced
|
||||
- [ ] Monitoring: Alerts for job backlog, API latency, cache hit rate, webhook failures
|
||||
- [ ] Alpaca price feed staleness: Should be <5s
|
||||
|
||||
**Cost estimation (steady state):**
|
||||
|
||||
| Service | Cost | Notes |
|
||||
|---------|------|-------|
|
||||
| Polygon.io (real-time news + quotes) | $200 | Required for webhooks |
|
||||
| Anthropic Claude API (w/ prompt caching) | $50–100 | Most cached; 90% cost reduction |
|
||||
| OpenAI API (fallback, optional) | $50 | Only if GPT-4 fallback added |
|
||||
| Alpaca/Interactive Brokers | $30–100 | Depends on which feed |
|
||||
| BullMQ (Redis queue, if scaled) | $0–30 | Free if self-hosted |
|
||||
| **Total** | **~$330–450/month** | Scales well (no per-user seat cost) |
|
||||
|
||||
---
|
||||
|
||||
## Final Architecture Summary
|
||||
|
||||
| Layer | Tech | Status |
|
||||
|-------|------|--------|
|
||||
| **Auth** | JWT + RBAC | Phase 11 (weeks 1-2) |
|
||||
| **Data** | SQLite → Postgres if 1000+ users | Phase 11 |
|
||||
| **News** | Polygon.io webhooks | Phase 12 (weeks 3-4) |
|
||||
| **LLM** | Anthropic + OpenAI w/ prompt caching | Phase 13-14 (weeks 5-6) |
|
||||
| **Trading** | Real-time price monitoring + Discord | Phase 14 (weeks 7-10) |
|
||||
| **Tracking** | Trade journal + stats | Phase 15 (weeks 11-12) |
|
||||
| **UI** | Svelte 5 + Phase 10 structure | Phase 10 (weeks 1-5 parallel) |
|
||||
|
||||
**Total time to "trading ready":** 12-16 weeks solo, 8 weeks with 1-2 junior devs.
|
||||
|
||||
**Go-live target:** Q3 2026 (July–September).
|
||||
|
||||
---
|
||||
|
||||
## Postgres Migration Path (When Needed)
|
||||
|
||||
If you grow to 10+ active traders:
|
||||
|
||||
1. Create Postgres RDS instance (AWS: ~$15/mo, db.t3.micro)
|
||||
2. Update connection string to point to Postgres
|
||||
3. Run schema dump SQLite → Postgres
|
||||
4. Test on staging first
|
||||
5. Blue-green deploy: run both DBs in parallel for 1 day, switch, keep SQLite as backup
|
||||
|
||||
**Time:** 2–4 hours. No code changes needed.
|
||||
|
||||
---
|
||||
|
||||
## Frequently Asked Questions
|
||||
|
||||
**Q: How many traders can this system handle?**
|
||||
|
||||
A:
|
||||
- **10–50 traders:** Single instance. Costs ~$450/mo.
|
||||
- **50–500 traders:** Add Postgres + Redis queue. Costs ~$1000/mo.
|
||||
- **500+ traders:** Add Kubernetes + load balancing. Costs ~$5000+/mo.
|
||||
|
||||
**Q: What if Polygon.io goes down?**
|
||||
|
||||
A: Have fallback plan:
|
||||
1. Switch to Finnhub webhooks (similar API, different provider)
|
||||
2. Or fall back to polling (5s instead of real-time, less expensive)
|
||||
3. Add circuit breaker: if Polygon fails for >5 min, automatically switch
|
||||
|
||||
**Q: Can I trade with real money?**
|
||||
|
||||
A: Yes, but:
|
||||
1. Start with **paper trading** (Alpaca's paper account, no real money)
|
||||
2. Test for 2+ weeks on real market conditions
|
||||
3. Once you hit 55%+ win rate on paper, go live with small position sizes
|
||||
4. Scale up gradually (1% → 5% → 10%)
|
||||
5. Always have manual kill-switch
|
||||
|
||||
**Q: Should I use local LLM training?**
|
||||
|
||||
A: Not yet. Only consider if:
|
||||
- You have 6+ months of clean trade data
|
||||
- Your LLM bill is >$1000/mo
|
||||
- You have $20K+ to spend on GPU infrastructure
|
||||
|
||||
For now, optimize prompts instead. Good prompt beats fine-tuned model.
|
||||
Reference in New Issue
Block a user