Trading Guides

🚀 Getting Started with TradingView Integration

What You’ll Learn

How to set up webhook connections
Understanding the Algo Trade Analytics webhook format
Creating your first automated strategy
Testing and debugging your setup

Step 1: Understanding the Basics

Algo Trade Analytics uses webhooks to receive trading signals from TradingView. When your strategy generates a signal, TradingView sends a webhook to Algo Trade Analytics, which then executes the trade on Alpaca.

The Process:

TradingView Signal → Algo Trade Analytics Webhook → Alpaca Execution

Step 2: Basic Pine Script Example

Here’s a complete Pine Script example that implements the Algo Trade Analytics webhook format:

//@version=6
strategy("Algo Trade Analytics Basic Strategy", overlay=true)

// Webhook configuration
authKey = "your_auth_key_here"
ticker = syminfo.ticker

// Simple moving average strategy
length = input.int(20, "MA Length")
ma = ta.sma(close, length)

// Entry conditions
longCondition = ta.crossover(close, ma)
shortCondition = ta.crossunder(close, ma)

// Create webhook messages
longMessage = '{"ticker":"' + ticker +
  '","direction":"long","auth_key":"' + authKey +
  '","orderType":"market","qty":100}'

shortMessage = '{"ticker":"' + ticker +
  '","direction":"short","auth_key":"' + authKey +
  '","orderType":"market","qty":100}'

// Execute trades with webhooks
if longCondition
    strategy.entry("Long", strategy.long, alert_message=longMessage)
if shortCondition
    strategy.entry("Short", strategy.short, alert_message=shortMessage)

Next Steps

Test your setup with paper trading first
Monitor the webhook logs for successful connections
Explore advanced order types and risk management
Check out our advanced strategy examples

📝 Pine Script Fundamentals for Algo Trade Analytics

Algo Trade Analytics Webhook Format

Algo Trade Analytics uses a specific webhook format. Here are the key fields:

Required Fields

ticker - Stock symbol
direction - “long” or “short”
auth_key - Authentication key

Optional Fields

qty - Share quantity
orderType - Order type
stopPrice - Stop price
limitPrice - Limit price

Advanced Pine Script Example

//@version=6
strategy("Advanced Algo Trade Analytics Strategy", overlay=true)

// Configuration
authKey = input.string("your_auth_key", "Auth Key")
baseQty = input.int(100, "Base Quantity")
riskPercent = input.float(2.0, "Risk Percent", minval=0.1, maxval=10.0)

// Indicators
ema20 = ta.ema(close, 20)
ema50 = ta.ema(close, 50)
rsi = ta.rsi(close, 14)

// Entry conditions
longCondition = ta.crossover(ema20, ema50) and rsi < 70
shortCondition = ta.crossunder(ema20, ema50) and rsi > 30

// Risk management
stopLossPercent = 2.0
takeProfitPercent = 4.0

// Calculate position size based on risk
stopLoss = longCondition ? close * (1 - stopLossPercent/100) :
           shortCondition ? close * (1 + stopLossPercent/100) : na

accountEquity = 100000 // Replace with your account size
riskAmount = accountEquity * (riskPercent / 100)
stopDistance = math.abs(close - stopLoss)
qty = math.floor(riskAmount / stopDistance)

// Webhook messages with stop losses
longMessage = '{"ticker":"' + syminfo.ticker +
  '","direction":"long","auth_key":"' + authKey +
  '","orderType":"stop_limit","qty":' + str.tostring(qty) +
  ',"stopPrice":' + str.tostring(stopLoss) + '}'

if longCondition
    strategy.entry("Long", strategy.long, qty=qty, alert_message=longMessage)
    strategy.exit("Exit Long", "Long", stop=stopLoss, limit=close * (1 + takeProfitPercent/100))

🛡️ Risk Management and Position Sizing

Position Sizing Methods

Fixed Dollar Risk

Risk the same dollar amount on each trade:

riskAmount = 500 // $500 per trade
stopDistance = math.abs(close - stopLoss)
qty = math.floor(riskAmount / stopDistance)

Percentage Risk

Risk a percentage of account equity:

riskPercent = 2.0 // 2% of account
accountEquity = 100000
riskAmount = accountEquity * (riskPercent / 100)
qty = math.floor(riskAmount / stopDistance)

Risk Management Checklist

Never risk more than 1-2% of account per trade
Always use stop losses
Size positions based on stop distance
Consider correlation between positions
Have a maximum daily/weekly loss limit
Test all strategies with paper trading first

🔧 Testing and Debugging Strategies

Testing Workflow

Backtest in TradingView
- Test your strategy logic with historical data
Validate Webhook Format
- Use Algo Trade Analytics’ webhook tester
Paper Trading
- Test with live data but simulated trades
Small Position Live Test
- Start with minimal position sizes

Webhook Testing Tools

Built-in Tester

Validates JSON format
Tests authentication
Simulates trade execution

Webhook Logs

See all webhook attempts
Check response codes
Review error messages

Best Practices

Always test with paper trading first
Use version control for your Pine Script code
Keep detailed logs of your testing process
Test edge cases and error conditions
Monitor performance metrics continuously

📊 Advanced Order Types

Market Orders

{
  "ticker": "AAPL",
  "direction": "long",
  "auth_key": "your_key",
  "orderType": "market",
  "qty": 100
}

Limit Orders

{
  "ticker": "AAPL",
  "direction": "long",
  "auth_key": "your_key",
  "orderType": "limit",
  "limitPrice": 150.00,
  "qty": 100
}

Stop-Loss Orders

{
  "ticker": "AAPL",
  "direction": "short",
  "auth_key": "your_key",
  "orderType": "stop",
  "stopPrice": 145.00,
  "qty": 100
}

Stop-Limit Orders

{
  "ticker": "AAPL",
  "direction": "short",
  "auth_key": "your_key",
  "orderType": "stop_limit",
  "stopPrice": 145.00,
  "limitPrice": 144.50,
  "qty": 100
}

🎯 Strategy Examples

Mean Reversion Strategy

//@version=6
strategy("Mean Reversion", overlay=true)

// Bollinger Bands mean reversion
length = 20
mult = 2.0
basis = ta.sma(close, length)
dev = mult * ta.stdev(close, length)
upper = basis + dev
lower = basis - dev

// Entry conditions
longCondition = close < lower
shortCondition = close > upper

// Exit conditions
longExit = close > basis
shortExit = close < basis

// Webhook implementation
authKey = "your_auth_key"
longMessage = '{"ticker":"' + syminfo.ticker + '","direction":"long","auth_key":"' + authKey + '"}'
shortMessage = '{"ticker":"' + syminfo.ticker + '","direction":"short","auth_key":"' + authKey + '"}'

if longCondition
    strategy.entry("Long", strategy.long, alert_message=longMessage)
if longExit
    strategy.close("Long")

Breakout Strategy

//@version=6
strategy("Breakout Strategy", overlay=true)

// Donchian Channel breakout
length = 20
upper = ta.highest(high, length)
lower = ta.lowest(low, length)

// Entry conditions
longCondition = close > upper[1]
shortCondition = close < lower[1]

// Webhook messages
authKey = "your_auth_key"
qty = 100

longMessage = '{"ticker":"' + syminfo.ticker +
  '","direction":"long","auth_key":"' + authKey +
  '","qty":' + str.tostring(qty) + '}'

if longCondition
    strategy.entry("Long", strategy.long, alert_message=longMessage)

📈 Performance Optimization

Reducing Slippage

Use limit orders when possible
Avoid trading during low liquidity periods
Consider market impact for large positions
Monitor bid-ask spreads

Improving Fill Rates

Set realistic limit prices
Use stop-limit orders instead of stop orders
Consider time-in-force parameters
Monitor order execution quality

Monitoring and Alerts

Set up real-time performance alerts
Monitor drawdown levels
Track hit rates and slippage
Review execution quality regularly

Knowledge Base - FAQ and troubleshooting
Algo Trade Analytics Webhook API - Complete API specification
Integration Guide - Technical implementation
Risk Management - Advanced risk control