Serverless algorithmic trading — forged on AWS Lambda.
No servers. No babysitting. No cloud bill.
LambdaForge is a production-grade, fully serverless algorithmic stock trading bot. It runs entirely on AWS Lambda — no always-on server, no manual babysitting. EventBridge wakes it up on schedule, it scans a 200+ symbol watchlist, enforces 6-rule risk management, places trades through the Alpaca API, and emails you a digest. When the market closes, it goes back to sleep.
Paper trading is free. You can run this at ~$0/month using AWS Free Tier and Alpaca's paper trading account.
┌─────────────────────────────────────┐
Market opens │ AWS EventBridge │
09:30 ET ────────►│ Triggers Lambda on schedule │
└──────────────┬──────────────────────┘
│
┌──────────────▼──────────────────────┐
│ AWS Lambda (ARM64) │
│ • Scans 200+ symbols │
│ • Runs 3 of 7 built-in strategies │
│ • Enforces 6 risk rules │
│ • Places orders via Alpaca │
│ • Sends email digest │
└──────────────┬──────────────────────┘
│
┌───────────────────────┼──────────────────────┐
│ │ │
┌──────▼──────┐ ┌───────▼──────┐ ┌───────▼──────┐
│ S3 Bucket │ │ SSM Params │ │ Alpaca API │
│ trades.db │ │ (no deploy │ │ paper/live │
│ persisted │ │ needed) │ │ │
└─────────────┘ └──────────────┘ └──────────────┘
| Requirement | Notes |
|---|---|
| 🦙 Alpaca account | Free. Paper trading requires no deposit. Live trading requires a funded account. |
| ☁️ AWS account | Free tier covers everything at paper trading volumes |
| 🐳 Docker | Required to build Lambda container images |
| 🐍 Python 3.9+ | Lambda runtime constraint |
| 🔧 AWS SAM CLI | For building and deploying |
| ⚙️ AWS CLI | Configured with aws configure |
One of LambdaForge's biggest advantages: it costs almost nothing to run.
| AWS Service | What LambdaForge uses | Free Tier | Estimated cost |
|---|---|---|---|
| Lambda | 6 functions, ~1M invocations/month | 1M req + 400K GB-s free | $0 |
| EventBridge | 5 scheduled rules | 14M events free | $0 |
| S3 | 2–12 MB trades.db, re-uploaded up to once a minute (noncurrent versions expire after 3 days, 5 newest kept; weekly audit exports go straight to Glacier Deep Archive for 7 years) |
5 GB free | $0 |
| SSM Parameter Store | 12 parameters, ~3K reads/month | 10K API calls free | $0 |
| SNS | < 1K email notifications/month | 1K emails free | $0 |
| KMS | SecureString decryption on cold starts | 20K requests free | ~$0.15 |
| SES | HTML trade digest emails | 3K emails/month free | $0 |
| ECR | Container image storage | 500 MB free | $0 |
| Monthly total → | ~$0.15 |
Running 3 stacks (paper + live + experimental) in parallel costs ~$0.50/month. Still cheaper than a cup of coffee.
Compare this to a VPS or dedicated server which would run $5–$50/month for equivalent uptime.
| Feature | Details |
|---|---|
| 🧠 7 trading strategies (3 enabled by default) | MACD, Bollinger Squeeze, Z-Score Mean Reversion (enabled); RSI Confluence, EMA Crossover + ADX, RSI + MACD Confluence, Relative Strength vs SPY (available via config.json) |
| 🛡️ 6-rule risk manager | Confidence gate, daily loss limit, max positions, concentration cap, stop-loss enforcement, dynamic position sizing |
| 📈 Trailing stop-loss | Hybrid trailing stop — the tighter of 5% below the high-water mark or 2×ATR — re-evaluated every minute during market hours, never moves down |
| 🔴 Kill switch | One command liquidates everything and halts trading instantly |
| 📊 Multi-stack | Paper and live run as independent stacks — no shared state |
| 📧 Email digests | Hourly trade summaries, daily P&L snapshots, weekly performance reports |
| ⚙️ Zero-redeploy config | Tune risk params and flip the kill switch via SSM — no deploy needed |
| 🔒 Buy deduplication | Prevents duplicate orders while still allowing pyramiding into winning positions |
| 🕐 Market hours guard | Checks Alpaca's market clock on every run — skips holidays, half-days, and anything outside 09:30–16:00 ET (weekday/time heuristic as fallback) |
| 🏷️ Environment tagging | Email subjects prefixed [PAPER], [LIVE], [BOT-2] for easy inbox filtering |
git clone https://github.com/vishwakt/LambdaForge.git
cd LambdaForge
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt -r requirements-dev.txtcp .env.example .env
# Edit .env — add your Alpaca paper trading API keys# Core credentials (required)
aws ssm put-parameter --name "/stock-bot/alpaca_api_key" \
--value "YOUR_ALPACA_KEY" --type SecureString
aws ssm put-parameter --name "/stock-bot/alpaca_secret_key" \
--value "YOUR_ALPACA_SECRET" --type SecureString
aws ssm put-parameter --name "/stock-bot/notification_email" \
--value "you@example.com" --type String
aws ssm put-parameter --name "/stock-bot/trading_mode" \
--value "paper" --type Stringaws ses verify-email-identity --email-address you@example.com
# Check your inbox and click the verification linkcp samconfig.toml.example samconfig.toml
sam build
sam deploy --guided # First time — sets up ECR repos and S3 bucket
sam deploy # Subsequent deploysIf you passed NotificationEmail at deploy time, SAM already created the subscription — confirm it from the email SNS sends you. Otherwise: SNS → Topics → the topic whose display name is "Stock Trading Bot Alerts (paper)" → Create subscription → Email.
./scripts/test-lambdas.sh stock-trading-botAll strategies implement a common interface — they receive historical OHLCV bars and return a signal with action, confidence, stop_loss, and take_profit.
| Strategy | Entry Signal | Stop Loss | Take Profit | Best for |
|---|---|---|---|---|
| MACD Crossover | 12/26 EMA bullish cross + signal line | 3% below entry | 6% above | Trending markets |
| Bollinger Squeeze | Band compression → breakout + volume | Middle band (20-SMA) | 1:1 measured move above entry | Volatility expansion |
| Z-Score Mean Reversion | 50-day Z-score < −2 (oversold) | 1 std-dev below entry | Rolling mean (Z ≈ 0); SELL signal at Z > +2 | Range-bound markets |
| RSI Confluence | RSI oversold + uptrend + volume | 4% below entry | 8% above | Momentum dips |
| EMA Crossover + ADX | 9/21 EMA cross + ADX > 25 | 3% below entry | 6% above | Strong trends |
| RSI + MACD Confluence | RSI oversold + MACD bullish cross | 4% below entry | 8% above | Reversal signals |
| Relative Strength vs SPY | Outperforming SPY on rolling basis | 5% below entry | 10% above | Sector leaders |
Trailing stops are managed centrally — once a position is open, the stop price ratchets up automatically as price rises.
Want to add your own? See CONTRIBUTING.md — it takes ~50 lines of code.
All runtime configuration lives in AWS SSM Parameter Store — change anything without redeploying.
# Example: tighten risk limits without redeploying
aws ssm put-parameter --name "/stock-bot/max_positions" --value "8" --type String --overwrite
aws ssm put-parameter --name "/stock-bot/trailing_stop_pct" --value "0.03" --type String --overwrite| Parameter | Default | Description |
|---|---|---|
max_positions |
12 |
Max simultaneous open positions |
trailing_stop_pct |
0.05 |
Trailing stop as fraction of price |
max_concentration |
0.15 |
Max portfolio fraction per symbol |
max_daily_loss |
0.02 |
Daily loss limit — stops trading if hit |
min_confidence |
0.5 |
Minimum signal confidence to trade |
monitor_interval |
1 |
MonitorStops interval in minutes |
notify_frequency |
hourly |
realtime, hourly, or daily |
kill-switch |
alive |
Set to kill to halt all trading immediately |
Emergency halt — stops all trading and liquidates all positions within 1 minute.
# Get function name from your stack
KILL_FN=$(aws cloudformation describe-stacks --stack-name stock-trading-bot \
--query "Stacks[0].Outputs[?OutputKey=='KillSwitchFunctionName'].OutputValue" \
--output text)
# Check status
aws lambda invoke --function-name $KILL_FN \
--cli-binary-format raw-in-base64-out \
--payload '{"action":"status"}' /tmp/out.json && cat /tmp/out.json
# 🛑 ENGAGE — liquidate everything and halt
aws lambda invoke --function-name $KILL_FN \
--cli-binary-format raw-in-base64-out \
--payload '{"action":"kill"}' /tmp/out.json && cat /tmp/out.json
# ✅ DISENGAGE — resume normal trading
aws lambda invoke --function-name $KILL_FN \
--cli-binary-format raw-in-base64-out \
--payload '{"action":"alive"}' /tmp/out.json && cat /tmp/out.jsonNo CLI? Set /stock-bot/kill-switch → kill directly in the AWS Console. The next Lambda invocation picks it up.
A Telegram bot can operate any stack by name. Create a bot with
@BotFather, message it once, read your chat ID from
https://api.telegram.org/bot<TOKEN>/getUpdates, and put both in .env:
TELEGRAM_BOT_TOKEN=...
TELEGRAM_ALLOWED_CHAT_IDS=<your chat id>
Then run the poller on any machine with AWS CLI credentials for the account:
python -m src.telegram_bot| Message | Effect |
|---|---|
/bots |
List bots and commands |
/stock-bot-2 status |
Kill-switch state, equity, cash, open positions |
/stock-bot-2 positions |
Open positions with unrealized P&L |
/stock-bot-2 kill |
Shows what would be liquidated and asks you to confirm |
/stock-bot-2 kill confirm |
Invokes that stack's KillSwitchFunction: cancels orders, sells everything, halts |
/stock-bot-2 alive |
Resumes trading |
Bot names are the SSM prefixes without slashes: stock-bot, stock-bot-2,
stock-bot-live. Only chat IDs on the allowlist get a reply; anyone else is
ignored silently. kill runs inside the target stack's own Lambda, so the
poller never needs Alpaca credentials of its own — it needs
cloudformation:DescribeStacks, lambda:InvokeFunction, and SSM read/write
on the stack prefixes, all of which the deployer policy already grants.
Six Lambda functions — five on EventBridge schedules, plus a manually invoked kill switch:
| Function | Schedule | Purpose |
|---|---|---|
DailyScan |
09:30 ET weekdays | Full scan: exits, entries, risk checks |
MonitorStops |
Every 1 min (market hours) | Trailing stop enforcement + opportunistic entries |
EodSnapshot |
15:55 ET weekdays | End-of-day P&L + benchmark comparison |
WeeklyDigest |
Friday 15:55 ET | Weekly performance report |
HourlyDigest |
Hourly (market hours) | Consolidated trade activity digest |
KillSwitch |
Manual invoke | Emergency halt — liquidates everything |
Schedules run on EventBridge Scheduler with
ScheduleExpressionTimezone: America/New_York, so these times hold across daylight-saving transitions.
For the full architecture deep-dive including data flow diagrams, SQLite schema, and multi-stack setup: ARCHITECTURE.md.
python -m pytest tests/ -v106 tests covering market hours, buy deduplication and fill reconciliation, strategy signal generation, SSM caching, environment labelling, config defaults, trade statistics, and the weekly audit archive.
Pull requests welcome — especially new trading strategies. See CONTRIBUTING.md for the full guide, including the step-by-step process for adding a strategy in ~30 lines of code.
This software is for educational purposes only. It is not financial advice. Trading stocks involves significant risk of loss. Always paper trade first and never risk money you cannot afford to lose. The authors are not responsible for any financial losses incurred through the use of this software.
MIT — see LICENSE.