LLM Stock Trader

⚠️ Warning: This software is provided for educational and informational purposes only. Nothing in this repository constitutes financial, investment, legal, or tax advice.

LLM Stock Trader

An autonomous, LLM-powered trading agent that runs 24/7 on Cloudflare Workers. (This is highly modified for of MAHORAGA.

LLM Stock Trader monitors social sentiment from StockTwits and Reddit, uses AI (OpenAI, Anthropic, Google, xAI, DeepSeek via AI SDK, or 300+ models via OpenRouter) to analyze signals, and executes trades through Alpaca. It runs as a Cloudflare Durable Object with persistent state, automatic restarts, and 24/7 crypto trading support.

Features

24/7 Operation — Runs on Cloudflare Workers, no local machine required
Multi-Source Signals — StockTwits, Reddit (9 subreddits), Finnhub (news, insider, upgrades), FMP screener, SEC (8-K + Form 4), QuiverQuant, Alpaca screener & news, Twitter confirmation
Multi-Provider LLM — OpenAI, Anthropic, Google, xAI, DeepSeek via AI SDK, OpenRouter (300+ models), or Cloudflare AI Gateway
Crypto Trading — Trade BTC, ETH, SOL around the clock
Options Support — High-conviction options plays
Staleness Detection — Auto-exit positions that lose momentum
Pre-Market Analysis — Prepare trading plans before market open
Discord Notifications — Get alerts on BUY signals
Fully Customizable — Well-documented with [TUNE] and [CUSTOMIZABLE] markers

Requirements

Node.js 18+
Cloudflare account (free tier works)
Alpaca account (free, paper trading supported)
LLM API key (OpenAI, Anthropic, Google, xAI, DeepSeek), OpenRouter API key, or Cloudflare AI Gateway credentials

Quick Start

1. Clone and install

git clone https://github.com/ygwyg/LLM Stock Trader.git
cd LLM Stock Trader
npm install
cd dashboard && npm install && cd ..

2. Create Cloudflare resources

# Create D1 database
npx wrangler d1 create LLM Stock Trader-db
# Copy the database_id to wrangler.jsonc

# Create KV namespace
npx wrangler kv namespace create CACHE
# Copy the id to wrangler.jsonc

# Run migrations
npx wrangler d1 migrations apply LLM Stock Trader-db

3. Set secrets

# Required
npx wrangler secret put ALPACA_API_KEY
npx wrangler secret put ALPACA_API_SECRET

# API Authentication - generate a secure random token (64+ chars recommended)
# Example: openssl rand -base64 48
npx wrangler secret put LLM Stock Trader_API_TOKEN

# LLM Provider (choose one mode)
npx wrangler secret put LLM_PROVIDER  # "openai-raw" (default), "openrouter", "ai-sdk", or "cloudflare-gateway"
npx wrangler secret put LLM_MODEL     # e.g. "gpt-4o-mini" or "openai/gpt-5-mini" (OpenRouter)

# LLM API Keys (based on provider mode)
npx wrangler secret put OPENAI_API_KEY         # For openai-raw, openrouter, or ai-sdk with OpenAI
npx wrangler secret put OPENAI_BASE_URL        # Optional: override base URL (auto-set for openrouter)
# npx wrangler secret put ANTHROPIC_API_KEY    # For ai-sdk with Anthropic
# npx wrangler secret put GOOGLE_GENERATIVE_AI_API_KEY  # For ai-sdk with Google
# npx wrangler secret put XAI_API_KEY          # For ai-sdk with xAI/Grok
# npx wrangler secret put DEEPSEEK_API_KEY     # For ai-sdk with DeepSeek
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_ACCOUNT_ID  # For cloudflare-gateway
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_ID          # For cloudflare-gateway
# npx wrangler secret put CLOUDFLARE_AI_GATEWAY_TOKEN       # For cloudflare-gateway

# Optional
npx wrangler secret put ALPACA_PAPER         # "true" for paper trading (recommended)
npx wrangler secret put TWITTER_BEARER_TOKEN
npx wrangler secret put DISCORD_WEBHOOK_URL
npx wrangler secret put KILL_SWITCH_SECRET   # Emergency kill switch (separate from API token)

# Optional: Market data and signal providers
npx wrangler secret put FINNHUB_API_KEY      # Equity fundamentals + signal gatherer (free: https://finnhub.io/register)
npx wrangler secret put FMP_API_KEY          # Crypto market data + screener signals (free: https://financialmodelingprep.com/register)
npx wrangler secret put QUIVER_API_KEY       # QuiverQuant sentiment/fundamentals (optional, for gatherQuiverQuant)

4. Deploy

npx wrangler deploy

5. Enable the agent

All API endpoints require authentication via Bearer token:

# Set your API token as an env var for convenience
export LLM Stock Trader_TOKEN="your-api-token"

# Enable the agent
curl -H "Authorization: Bearer $LLM Stock Trader_TOKEN" \
  https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/enable

6. Monitor

# Check status
curl -H "Authorization: Bearer $LLM Stock Trader_TOKEN" \
  https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/status

# View logs
curl -H "Authorization: Bearer $LLM Stock Trader_TOKEN" \
  https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/logs

# Emergency kill switch (uses separate KILL_SWITCH_SECRET)
curl -H "Authorization: Bearer $KILL_SWITCH_SECRET" \
  https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/kill

# Run dashboard locally (or use ./start for both backend + dashboard)
cd dashboard && npm install && npm run dev

Local Development

Quick start (single command)

# Copy config files (first time only)
cp .env.example .dev.vars        # Edit with your API keys
cp wrangler.example.jsonc wrangler.jsonc

# Auto-authenticate the dashboard (optional, avoids manual token entry)
echo "VITE_LLM Stock Trader_API_TOKEN=$(grep LLM Stock Trader_API_TOKEN .dev.vars | cut -d= -f2-)" > dashboard/.env.development

# Run local D1 migrations
npm run db:migrate

# Start both backend and dashboard
./start

This starts the Wrangler backend on http://localhost:8787 and the React dashboard on http://localhost:3000. Press Ctrl+C to stop both.

The dashboard/.env.development file auto-injects your API token so the dashboard authenticates without manual entry. Without it, you'll need to paste your LLM Stock Trader_API_TOKEN into the dashboard login screen on first visit.

./start              # Start both backend + dashboard
./start backend      # Backend only (port 8787)
./start dashboard    # Dashboard only (port 3000)

Manual start (separate terminals)

# Terminal 1 - Start wrangler
npm run dev

# Terminal 2 - Start dashboard
cd dashboard && npm run dev

Test Alpaca connection

npm run test:alpaca

Verifies your Alpaca API keys by testing account authentication, market clock, and a live AAPL snapshot.

List OpenRouter models

./scripts/list-models.sh

Fetches all 300+ OpenRouter models with pricing and writes them to scripts/openrouter-models.json, sorted by cost (cheapest first).

Enable the agent

curl -H "Authorization: Bearer $LLM Stock Trader_TOKEN" \
  http://localhost:8787/agent/enable

Customizing the Harness

The main trading logic is in src/durable-objects/LLM Stock Trader-harness.ts. It's documented with markers to help you find what to modify:

Marker	Meaning
`[TUNE]`	Numeric values you can adjust
`[TOGGLE]`	Features you can enable/disable
`[CUSTOMIZABLE]`	Sections with code you might want to modify

Adding a New Data Source

Create a new gather*() method that returns Signal[]
Add it to runDataGatherers() Promise.all
Add source weight to SOURCE_CONFIG.weights

See docs/harness.html for detailed customization guide.

Configuration

Setting	Default	Description
`max_positions`	5	Maximum concurrent positions
`max_position_value`	5000	Maximum $ per position
`take_profit_pct`	10	Take profit percentage
`stop_loss_pct`	5	Stop loss percentage
`min_sentiment_score`	0.3	Minimum sentiment to consider
`min_analyst_confidence`	0.6	Minimum LLM confidence to trade
`options_enabled`	false	Enable options trading
`crypto_enabled`	false	Enable 24/7 crypto trading
`llm_model`	gpt-4o-mini	Research model. Use full ID for OpenRouter, e.g. `openai/gpt-5-mini`
`llm_analyst_model`	gpt-4o	Analyst model. Use full ID for OpenRouter, e.g. `openai/gpt-5.2`

LLM Provider Configuration

LLM Stock Trader supports multiple LLM providers via four modes:

Mode	Description	Required Env Vars
`openai-raw`	Direct OpenAI API (default)	`OPENAI_API_KEY`
`openrouter`	OpenRouter proxy (300+ models)	`OPENAI_API_KEY` (your OpenRouter key)
`ai-sdk`	Vercel AI SDK with 5 providers	One or more provider keys
`cloudflare-gateway`	Cloudflare AI Gateway (/compat)	`CLOUDFLARE_AI_GATEWAY_ACCOUNT_ID`, `CLOUDFLARE_AI_GATEWAY_ID`, `CLOUDFLARE_AI_GATEWAY_TOKEN`

OpenRouter Setup:

OpenRouter gives you access to 300+ models (OpenAI, Anthropic, Google, Meta, DeepSeek, xAI, and more) through a single API key. Get your key at openrouter.ai/keys.

Free model support: LLM Stock Trader automatically detects free-tier models (model IDs containing :free or /free) and applies 8-second rate limiting between LLM calls to respect free-tier rate limits. If a model does not support system prompts (e.g., some Gemma variants via the openrouter/free endpoint), LLM Stock Trader automatically retries by converting system instructions into user message prefixes. Cost tracking correctly reports $0.00 (free) for these models.

# .dev.vars (local) or wrangler secrets (production)
LLM_PROVIDER=openrouter
LLM_MODEL=openai/gpt-5-mini
OPENAI_API_KEY=sk-or-v1-your-openrouter-key

Models use the provider/model format (e.g. openai/gpt-5-mini, anthropic/claude-sonnet-4.5, google/gemini-2.5-pro). The base URL is auto-configured to https://openrouter.ai/api/v1.

The dashboard settings panel includes a dynamic model picker when OpenRouter is selected -- it fetches all 300+ models with live pricing from the OpenRouter API, with search filtering and sort by price. LLM cost tracking uses actual costs from OpenRouter's API response, so free models correctly show $0.

Run ./scripts/list-models.sh to fetch all available models with pricing to a local JSON file, sorted by cost.

Optional OpenAI Base URL Override:

OPENAI_BASE_URL — Override the base URL for OpenAI requests. Applies to openai-raw and ai-sdk (OpenAI models). Auto-set for openrouter. Default: https://api.openai.com/v1.

Cloudflare AI Gateway Notes:

This integration calls Cloudflare's OpenAI-compatible /compat/chat/completions endpoint and always sends cf-aig-authorization.
It is intended for BYOK/Unified Billing setups where upstream provider keys are configured in Cloudflare (so your worker does not send provider API keys).
Models use the {provider}/{model} format (e.g. openai/gpt-5-mini, google-ai-studio/gemini-2.5-flash, anthropic/claude-sonnet-4-5).

AI SDK Supported Providers:

Provider	Env Var	Example Models
OpenAI	`OPENAI_API_KEY`	`openai/gpt-4o`, `openai/o1`
Anthropic	`ANTHROPIC_API_KEY`	`anthropic/claude-sonnet-4`, `anthropic/claude-opus-4`
Google	`GOOGLE_GENERATIVE_AI_API_KEY`	`google/gemini-2.5-pro`, `google/gemini-2.5-flash`
xAI (Grok)	`XAI_API_KEY`	`xai/grok-4`, `xai/grok-3`
DeepSeek	`DEEPSEEK_API_KEY`	`deepseek/deepseek-chat`, `deepseek/deepseek-reasoner`

Example: Using Claude via OpenRouter:

npx wrangler secret put LLM_PROVIDER  # Set to "openrouter"
npx wrangler secret put LLM_MODEL     # Set to "anthropic/claude-sonnet-4.5"
npx wrangler secret put OPENAI_API_KEY # Your OpenRouter API key (sk-or-...)

Example: Using Claude with AI SDK (direct):

npx wrangler secret put LLM_PROVIDER      # Set to "ai-sdk"
npx wrangler secret put LLM_MODEL         # Set to "anthropic/claude-sonnet-4"
npx wrangler secret put ANTHROPIC_API_KEY # Your Anthropic API key

Sentiment Analysis

LLM Stock Trader gathers social sentiment from multiple sources in parallel. The core pipeline requires no API keys — StockTwits and Reddit are public APIs.

Sources

Source	API Key Required	Role	Weight
StockTwits	No (public API)	Primary signal — 30 symbols, equities endpoint, Bullish/Bearish labels	0.85
Reddit	No (public API)	Primary signal — 9 subreddits, 50 posts each, keyword-based sentiment	0.6–0.9 per sub
Finnhub	Yes (`FINNHUB_API_KEY`)	News, insider transactions, analyst upgrades/downgrades	—
FMP	Yes (`FMP_API_KEY`)	Screeners — gainers, losers, most active	—
SEC EDGAR	No (public API)	8-K and Form 4 feeds (40 entries each), filing-based sentiment	—
QuiverQuant	Yes (`QUIVER_API_KEY`)	Alternative sentiment/fundamentals (when configured)	—
Alpaca Screener	Uses Alpaca key	Most actives, movers (when Alpaca configured)	—
Alpaca News	Uses Alpaca key	News feed for screened symbols (when Alpaca configured)	—
Twitter/X	Yes (`TWITTER_BEARER_TOKEN`)	Optional confirmation only — boosts existing signals	0.90–0.95
Crypto Momentum	No (uses Alpaca key)	Price-momentum-based sentiment for crypto assets	—

How It Works

Gather — runDataGatherers() fetches StockTwits trending symbols, Reddit hot posts (r/wallstreetbets, r/stocks, r/investing, r/options), SEC filings, and crypto momentum in parallel
Score — Each source applies weighting: time decay (exponential with 120-min half-life for Reddit), engagement multipliers (upvotes/comments), flair bonuses (DD posts get 1.5x, memes get 0.4x), and source-specific weights
Filter — Signals below min_sentiment_score (default 0.3) are dropped. StockTwits requires minimum 5 messages per symbol; Reddit requires minimum 2 mentions
Confirm (optional) — If TWITTER_BEARER_TOKEN is set, signals with sentiment >= 0.3 are checked against recent tweets with actionable keywords (unusual flow, sweep, whale, breaking, upgrade/downgrade). Matching Twitter sentiment boosts signal confidence
Research — Surviving signals are sent to the LLM for deep analysis and final BUY/SKIP/HOLD verdict

Market signal coverage expansion

The signal pipeline was expanded to include more data sources, higher limits, and better UX:

Data sources and gatherers

Finnhub — getUpgradeDowngrade(), getMarketNews(), getInsiderTransactions(); harness method gatherFinnhub() (requires FINNHUB_API_KEY).
FMP (Financial Modeling Prep) — getMarketGainers(), getMarketLosers(), getMostActive(); harness method gatherFMPScreener() (requires FMP_API_KEY).
SEC EDGAR — 8-K and Form 4 feeds, 40 entries each.
StockTwits — Up to 30 symbols, equities-specific endpoint.
Reddit — 5 additional subreddits (9 total), 50 posts per subreddit.
QuiverQuant — New provider and harness method gatherQuiverQuant() (optional; requires QUIVER_API_KEY when used).
Alpaca — New screener (most actives, movers) via gatherAlpacaScreener(), and gatherAlpacaNews() for news on screened symbols (uses existing Alpaca credentials).

Backend

MAX_SIGNALS increased to 500 (merged signals before research).
Deduplication of signals by symbol/source to avoid duplicate research.
Composite scoring improved for ranking which signals get researched.
Research limit (e.g. top 10) — only the top N signals by composite score are sent to the analyst LLM.

Frontend

No 20-signal cap — dashboard shows the full signal set (up to backend limit).
Source filter tabs — filter signals by source (e.g. StockTwits, Reddit, Finnhub).
Signal strength — indicators (e.g. STRONG) for high composite score.

Rate limiting

Centralized RateLimiter utility with per-provider budgets so all data providers respect API limits without blocking each other.

Logging

Application logs from the harness (this.log(agent, action, details)) are written to in-memory state.logs and also to console.log, so they appear in the session log files (e.g. logs/<timestamp>.log) when running ./start. Targeted logs for the analyst run, BUY+confidence filter, and Alpaca order submit can be added so the “BUY → attempt purchase” path is visible in those same log files.

Twitter Setup (Optional)

Twitter is not required for the sentiment pipeline — it only confirms signals that already passed the threshold. To enable it:

Create a developer account at developer.x.com
Generate a Bearer Token
Set the secret: npx wrangler secret put TWITTER_BEARER_TOKEN

Rate-limited to ~~200 reads/day (~~$1–2/day). Results are cached for 5 minutes.

StockTwits ──→ score × sourceWeight × freshness ──┐ Reddit ────→ rawSentiment × (timeDecay × engagement × flair × sourceWeight) ──┤ SEC ───────→ staticSentiment × sourceWeight × freshness ──┤ Crypto ────→ momentum-based rawSentiment ──────────────────┘ │ signalCache (top 200 by |sentiment|) │ ┌────────────────────┴─────────────────────┐ │ │ researchTopSignals() analyzeSignalsWithLLM() raw_sentiment >= 0.3 avgSentiment >= 0.15 top 5 → individual LLM top 10 → batch LLM │ │ └────────────────────┬─────────────────────┘ │ ┌── Twitter Confirm ──┐ │ +15% if confirms │ │ -15% if contradicts│ └────────┬────────────┘ │ confidence >= 0.6? │ executeBuy()

Discord Notifications

Set DISCORD_WEBHOOK_URL to receive real-time trade alerts as rich embeds in a Discord channel. This is optional — if not set, notifications are silently skipped.

What Gets Sent

Type	Trigger	Content
Signal alert	High sentiment detected for a symbol	Ticker, sentiment %, sources, "researching..." status
Research verdict	LLM returns a BUY verdict	Ticker, verdict (BUY/SKIP/HOLD), confidence %, entry quality, reasoning (truncated to 300 chars), catalysts, red flags

Notifications are rate-limited to one per symbol every 30 minutes to prevent spam.

Setup

In Discord: Channel Settings → Integrations → Webhooks → New Webhook
Copy the webhook URL
Set the secret: npx wrangler secret put DISCORD_WEBHOOK_URL

All embeds include a footer: "LLM Stock Trader • Not financial advice • DYOR"

API Endpoints

Endpoint	Description
`/agent/status`	Full status (account, positions, signals)
`/agent/enable`	Enable the agent
`/agent/disable`	Disable the agent
`/agent/config`	GET or POST configuration
`/agent/costs`	GET costs, or DELETE to reset cost tracker
`/agent/logs`	Get recent logs
`/agent/trigger`	Manually trigger (for testing)
`/agent/kill`	Emergency kill switch (uses `KILL_SWITCH_SECRET`)
`/agent/symbol-detail/:symbol`	On-demand market data for a symbol (tooltip data)
`/mcp`	MCP server for tool access

Security

API Authentication (Required)

All /agent/* endpoints require Bearer token authentication using LLM Stock Trader_API_TOKEN:

curl -H "Authorization: Bearer $LLM Stock Trader_TOKEN" https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/status

Generate a secure token: openssl rand -base64 48

Emergency Kill Switch

The /agent/kill endpoint uses a separate KILL_SWITCH_SECRET for emergency shutdown:

curl -H "Authorization: Bearer $KILL_SWITCH_SECRET" https://LLM Stock Trader.bernardoalmeida2004.workers.dev/agent/kill

This immediately disables the agent, cancels all alarms, and clears the signal cache.

Cloudflare Access (Recommended)

For additional security with SSO/email verification, set up Cloudflare Access:

# 1. Create a Cloudflare API token with Access:Edit permissions
#    https://dash.cloudflare.com/profile/api-tokens

# 2. Run the setup script
CLOUDFLARE_API_TOKEN=your-token \
CLOUDFLARE_ACCOUNT_ID=your-account-id \
LLM Stock Trader_WORKER_URL=https://LLM Stock Trader.your-subdomain.workers.dev \
LLM Stock Trader_ALLOWED_EMAILS=you@example.com \
npm run setup:access

This creates a Cloudflare Access Application with email verification or One-Time PIN.

Project Structure

LLM Stock Trader/
├── start                       # Dev launcher (backend + dashboard)
├── wrangler.jsonc              # Cloudflare Workers config
├── .dev.vars                   # Local secrets (gitignored)
├── src/
│   ├── index.ts                # Entry point
│   ├── durable-objects/
│   │   ├── LLM Stock Trader-harness.ts # THE HARNESS - customize this!
│   │   └── session.ts
│   ├── mcp/                    # MCP server & tools
│   ├── policy/                 # Trade validation
│   └── providers/              # Alpaca, LLM, Finnhub, FMP, news clients
├── scripts/
│   ├── test-alpaca.ts          # Alpaca API connection test
│   ├── list-models.sh          # Fetch OpenRouter models + pricing
│   └── setup-access.ts         # Cloudflare Access setup
├── dashboard/                  # React dashboard (Vite + React + Tailwind)
│   └── src/
│       ├── index.css           # Synthwave '84 theme, glow utilities, CRT overlay CSS
│       ├── components/         # Panel, LineChart, ModelPicker, CrtEffect, etc.
│       └── hooks/              # useOpenRouterModels (dynamic model fetching)
├── docs/                       # Documentation
└── migrations/                 # D1 database migrations

Dashboard Metrics & P&L Calculations

The Account panel displays several financial metrics. Some are passed through directly from the Alpaca API, while others are derived in the dashboard.

Data Sources

Metric	Source	Calculated By
Equity	Alpaca `/v2/account` → `equity`	Alpaca (direct)
Cash	Alpaca `/v2/account` → `cash`	Alpaca (direct)
Buying Power	Alpaca `/v2/account` → `buying_power`	Alpaca (direct)
Last Equity	Alpaca `/v2/account` → `last_equity`	Alpaca (direct)
Starting Equity	Alpaca `/v2/account/portfolio/history` → `base_value`	Auto-captured on first run
Unrealized P&L	Alpaca `/v2/positions` → sum of `unrealized_pl`	Dashboard
Daily P&L	Derived from equity and last_equity	Dashboard
Total P&L	Derived from equity and starting_equity	Dashboard
Realized P&L	Derived from total and unrealized P&L	Dashboard

Starting Equity

The starting_equity value is automatically derived from Alpaca on first run — it is not hardcoded. The harness calls Alpaca's Portfolio History API and reads the base_value field, which represents the account's initial funded value (e.g., $100,000 for a standard paper account).

Once captured, the value is persisted in the Durable Object config. To re-derive it from Alpaca (e.g., after a reset), use the Reset button next to "Starting Equity" in the Settings modal — this clears the persisted value so the next status poll re-fetches it.

Formulas

Daily P&L — change since previous trading day's close:

$$\text{Daily P&L} = \text{equity} - \text{last_equity}$$

$$\text{Daily P&L %} = \frac{\text{equity} - \text{last_equity}}{\text{last_equity}} \times 100$$

Total P&L — all-time change since account inception:

$$\text{Total P&L} = \text{equity} - \text{starting_equity}$$

$$\text{Total P&L %} = \frac{\text{equity} - \text{starting_equity}}{\text{starting_equity}} \times 100$$

Unrealized P&L — sum of gains/losses on open positions:

$$\text{Unrealized P&L} = \sum_{i=1}^{n} \text{position}_i.\text{unrealized_pl}$$

Realized P&L — derived from the accounting identity $\text{Total} = \text{Realized} + \text{Unrealized}$:

$$\text{Realized P&L} = \text{Total P&L} - \text{Unrealized P&L}$$

Example

For an account that started at $100,000 with current equity of $106,035:

Metric	Formula	Value
Starting Equity	Alpaca `base_value`	$100,000.00
Last Equity	Alpaca `last_equity` (prev close)	$100,000.00
Equity	Alpaca `equity`	$106,035.52
Daily P&L	$106{,}035.52 - 100{,}000$	$6,035.52 (+6.04%)
Total P&L	$106{,}035.52 - 100{,}000$	$6,035.52 (+6.04%)
Unrealized P&L	$\sum \text{positions}$	$6,278.21
Realized P&L	$6{,}035.52 - 6{,}278.21$	-$242.69

Note: Daily and Total P&L are identical on day 1 (when last_equity equals starting_equity). They diverge from day 2 onward as last_equity updates to each day's closing equity while starting_equity remains fixed.

Cash & Buying Power

Cash and Buying Power come directly from Alpaca's account API — the dashboard does not calculate these.

Cash — uninvested dollars in the account (starting cash minus cost of purchases plus proceeds from sales)
Buying Power — total amount available to open new positions, factoring in RegT margin. For a margin-eligible account this is typically ~2× settled cash, reduced by the margin requirements of existing positions

Positions Panel

The positions table shows all open positions with the following columns:

Column	Description
Symbol	Ticker symbol (crypto symbols show ₿ prefix). Hover for detailed tooltip.
Shares	Number of shares/units held
Value	Current market value of the position
Today P&L	Intraday unrealized profit/loss (uses `unrealized_intraday_pl`)
Total P&L	All-time unrealized profit/loss since entry (uses `unrealized_pl`)
Diversity	Position weight as a percentage of total portfolio value
Trend	Sparkline showing recent price movement

Symbol Tooltip

Hovering over a symbol in the positions table loads detailed market data on-demand from the /agent/symbol-detail/:symbol endpoint. Data is organized in sections:

Section	Fields	Source
Quote	Bid (price × size), Ask (price × size), Bid-Ask Spread	Alpaca snapshot
Trading	Volume, Overnight Volume (--), Average Volume	Alpaca snapshot + Finnhub
Price	Open, Today's High, Today's Low	Alpaca snapshot
Fundamentals	Market Cap, 52 Week High/Low, P/E Ratio, Dividend Yield	Finnhub (equities) or FMP (crypto)
Short Info	Short Inventory (Available/Unavailable), Borrow Rate (--)	Alpaca asset (equities only)
Position	Entry Price, Current Price, Hold Time, Entry Sentiment, Staleness	Existing position data

Data Providers

Finnhub provides equity fundamentals (market cap, P/E ratio, dividend yield, 52-week high/low, average volume) for all US stocks with no symbol restrictions.

Free tier: 60 calls/minute, no daily cap
Endpoint: /api/v1/stock/metric?symbol=X&metric=all
Data is cached in KV for 15 minutes

FMP (Financial Modeling Prep) provides crypto market data for major pairs (BTCUSD, ETHUSD, SOLUSD, etc.).

Free tier: 250 calls/day
Endpoint: /stable/quote?symbol=BTCUSD
Data is cached in KV for 5 minutes

Both providers are optional. If API keys are not configured, the respective fields show "--" in the tooltip. Alpaca data (bid/ask, volume, OHLC, shortable status) is always available.

Setting up Finnhub

Create a free account at https://finnhub.io/register
Copy your API key from the Finnhub dashboard
For local development: add FINNHUB_API_KEY=your_key to .dev.vars
For production: npx wrangler secret put FINNHUB_API_KEY

Setting up FMP

Create a free account at https://site.financialmodelingprep.com/register
Copy your API key from the FMP dashboard
For local development: add FMP_API_KEY=your_key to .dev.vars
For production: npx wrangler secret put FMP_API_KEY

Dashboard Theming

The dashboard uses a Synthwave '84 color palette with neon glow effects, defined as CSS custom properties in dashboard/src/index.css.

Color Palette

All colors are pulled from the Synthwave '84 VS Code theme:

@theme {
  /* Backgrounds — deep purple-blue */
  --color-hud-bg: #262335;
  --color-hud-bg-panel: #2a2139;

  /* Core accents */
  --color-hud-primary: #36f9f6;     /* Neon cyan */
  --color-hud-success: #72f1b8;     /* Neon green */
  --color-hud-warning: #fede5d;     /* Neon yellow */
  --color-hud-error: #fe4450;       /* Neon red */
  --color-hud-purple: #ff7edb;      /* Neon pink */
  --color-hud-cyan: #03edf9;        /* Bright cyan */

  /* Text */
  --color-hud-text: #b6b1b1;        /* Muted warm grey */
  --color-hud-text-dim: #848bbd;    /* Lavender */
  --color-hud-text-bright: #f4eee4; /* Off-white */
}

Neon Glow Effects

Text glow utilities (.glow-cyan, .glow-green, .glow-pink, .glow-red, .glow-yellow, .glow-orange) apply text-shadow halos inspired by the Synthwave '84 glow CSS. They're used on panel titles, status indicators, large metric values, and the header title. A pink-to-cyan gradient stripe (.neon-stripe) accents panel headers and dividers.

CRT Effect

A toggleable CRT screen effect is available via the [CRT] button in the top-left of the header. It adds:

Scanlines — Thin horizontal bars with a slow retrace scroll
Vignette — Radial gradient darkening screen edges
Static noise — Tiled noise texture animated via CSS
Flicker — Subtle brightness/contrast oscillation on the page
Chromatic aberration — Faint red/cyan fringe at screen edges

The effect is CSS-only with zero per-frame JavaScript (noise tile is generated once on mount). Inspired by CRTFilter.js. The preference is persisted to localStorage.

All overlay layers use pointer-events: none and high z-index so they never block interaction.

Safety Features

Feature	Description
Paper Trading	Start with `ALPACA_PAPER=true`
Kill Switch	Emergency halt via secret
Position Limits	Max positions and $ per position
Daily Loss Limit	Stops trading after 2% daily loss
Staleness Detection	Auto-exit stale positions
Duplicate Buy Prevention	Tracks recently ordered symbols for 5 minutes to prevent duplicate buys while orders are `pending_new`
Crypto/Stock Path Isolation	Analyst excludes crypto symbols from stock buy candidates, preventing double-buying through both the crypto and analyst execution paths
No Margin	Cash-only trading
No Shorting	Long positions only

Community

Join our Discord for help and discussion:

Discord Server

Disclaimer

⚠️ IMPORTANT: READ BEFORE USING

This software is provided for educational and informational purposes only. Nothing in this repository constitutes financial, investment, legal, or tax advice.

By using this software, you acknowledge and agree that:

All trading and investment decisions are made at your own risk
Markets are volatile and you can lose some or all of your capital
No guarantees of performance, profits, or outcomes are made
The authors and contributors are not responsible for any financial losses
This software may contain bugs or behave unexpectedly
Past performance does not guarantee future results

Always start with paper trading and never risk money you cannot afford to lose.

License

MIT License - Free for personal and commercial use. See LICENSE for full terms.

Name		Name	Last commit message	Last commit date
Latest commit History 140 Commits
.github/workflows		.github/workflows
dashboard		dashboard
docs		docs
migrations		migrations
scripts		scripts
src		src
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
MAHORAGA.code-workspace		MAHORAGA.code-workspace
README.md		README.md
agent-config.example.json		agent-config.example.json
biome.json		biome.json
how-it-works.md		how-it-works.md
package-lock.json		package-lock.json
package.json		package.json
start		start
tsconfig.json		tsconfig.json
vitest.config.ts		vitest.config.ts
wrangler.example.jsonc		wrangler.example.jsonc

Folders and files

Latest commit

History

Repository files navigation

LLM Stock Trader

Features

Requirements

Quick Start

1. Clone and install

2. Create Cloudflare resources

3. Set secrets

4. Deploy

5. Enable the agent

6. Monitor

Local Development

Quick start (single command)

Manual start (separate terminals)

Test Alpaca connection

List OpenRouter models

Enable the agent

Customizing the Harness

Adding a New Data Source

Configuration

LLM Provider Configuration

Sentiment Analysis

Sources

How It Works

Market signal coverage expansion

Twitter Setup (Optional)

Discord Notifications

What Gets Sent

Setup

API Endpoints

Security

API Authentication (Required)

Emergency Kill Switch

Cloudflare Access (Recommended)

Project Structure

Dashboard Metrics & P&L Calculations

Data Sources

Starting Equity

Formulas

Example

Cash & Buying Power

Positions Panel

Symbol Tooltip

Data Providers

Setting up Finnhub

Setting up FMP

Dashboard Theming

Color Palette

Neon Glow Effects

CRT Effect

Safety Features

Community

Disclaimer

License

About

Resources

License

Uh oh!

Stars

Watchers

Forks

Releases

Packages 0

Uh oh!

Contributors

Uh oh!

Languages

Packages