Your First Indicator

In this tutorial, you’ll build a simple Moving Average Crossover indicator that generates BUY/SELL signals on the InnovaTrading chart.

Prerequisites

An API key (contact us to get one)
Python 3.8+ or Node.js 16+
Basic understanding of trading concepts

What We’ll Build

A Moving Average Crossover indicator that:

Calculates 20-period and 50-period Simple Moving Averages
Generates a BUY signal when the fast MA crosses above the slow MA
Generates a SELL signal when the fast MA crosses below the slow MA

Step 1: Set Up Your Project

mkdir ma_crossover
cd ma_crossover
pip install requests pandas

mkdir ma_crossover
cd ma_crossover
npm init -y
npm install axios

Step 2: Create the Configuration

Create a config.py or config.js file:

API_KEY = "your_api_key_here"
BASE_URL = "https://api.innova-trading.com"

# Indicator settings
SYMBOL = "EURUSD"
TIMEFRAME = 60  # 1 hour
FAST_MA = 20
SLOW_MA = 50

module.exports = {
  API_KEY: "your_api_key_here",
  BASE_URL: "https://api.innova-trading.com",
  SYMBOL: "EURUSD",
  TIMEFRAME: 60,
  FAST_MA: 20,
  SLOW_MA: 50,
};

Step 3: Fetch Market Data

import requests
import pandas as pd
from config import API_KEY, BASE_URL, SYMBOL, TIMEFRAME

def get_bars(limit=100):
    """Fetch OHLC bars from the API."""
    url = f"{BASE_URL}/api/external/bars/{SYMBOL}/{TIMEFRAME}"
    headers = {"Authorization": f"Bearer {API_KEY}"}

    response = requests.get(url, params={"limit": limit}, headers=headers)
    response.raise_for_status()

    data = response.json()
    df = pd.DataFrame(data["bars"])
    return df

# Test it
if __name__ == "__main__":
    bars = get_bars(100)
    print(f"Fetched {len(bars)} bars")
    print(bars.tail())

const axios = require("axios");
const config = require("./config");

async function getBars(limit = 100) {
  const url = `${config.BASE_URL}/api/external/bars/${config.SYMBOL}/${config.TIMEFRAME}`;

  const response = await axios.get(url, {
    params: { limit },
    headers: { Authorization: `Bearer ${config.API_KEY}` },
  });

  return response.data.bars;
}

// Test it
(async () => {
  const bars = await getBars(100);
  console.log(`Fetched ${bars.length} bars`);
  console.log(bars.slice(-5));
})();

Run it to verify:

python main.py
# or
node main.js

Step 4: Calculate Moving Averages

from config import FAST_MA, SLOW_MA

def calculate_sma(df, period, column="close"):
    """Calculate Simple Moving Average."""
    return df[column].rolling(window=period).mean()

def add_moving_averages(df):
    """Add fast and slow MAs to dataframe."""
    df["fast_ma"] = calculate_sma(df, FAST_MA)
    df["slow_ma"] = calculate_sma(df, SLOW_MA)
    return df

# Test it
if __name__ == "__main__":
    bars = get_bars(100)
    bars = add_moving_averages(bars)
    print(bars[["time", "close", "fast_ma", "slow_ma"]].tail())

const config = require("./config");

function calculateSMA(bars, period, field = "close") {
  const result = [];
  for (let i = 0; i < bars.length; i++) {
    if (i < period - 1) {
      result.push(null);
    } else {
      const slice = bars.slice(i - period + 1, i + 1);
      const sum = slice.reduce((acc, bar) => acc + bar[field], 0);
      result.push(sum / period);
    }
  }
  return result;
}

function addMovingAverages(bars) {
  const fastMA = calculateSMA(bars, config.FAST_MA);
  const slowMA = calculateSMA(bars, config.SLOW_MA);

  return bars.map((bar, i) => ({
    ...bar,
    fast_ma: fastMA[i],
    slow_ma: slowMA[i],
  }));
}

Step 5: Detect Crossovers

def detect_crossovers(df):
    """
    Detect MA crossovers and generate signal points.

    Returns list of signal points in API format.
    """
    points = []

    for i in range(1, len(df)):
        prev = df.iloc[i - 1]
        curr = df.iloc[i]

        # Skip if MAs are not yet calculated
        if pd.isna(prev["fast_ma"]) or pd.isna(curr["slow_ma"]):
            continue

        # Bullish crossover: fast MA crosses above slow MA
        prev_diff = prev["fast_ma"] - prev["slow_ma"]
        curr_diff = curr["fast_ma"] - curr["slow_ma"]

        if prev_diff <= 0 and curr_diff > 0:
            # BUY signal
            points.append({
                "time": int(curr["time"]),
                "type": "low",
                "price": float(curr["low"]) - 0.0005,  # Slightly below candle
                "label": "BUY",
                "color": "#3b82f6",
                "shape": "arrowUp",
                "size": 2
            })

        elif prev_diff >= 0 and curr_diff < 0:
            # SELL signal
            points.append({
                "time": int(curr["time"]),
                "type": "high",
                "price": float(curr["high"]) + 0.0005,  # Slightly above candle
                "label": "SELL",
                "color": "#f97316",
                "shape": "arrowDown",
                "size": 2
            })

    return points

function detectCrossovers(bars) {
  const points = [];

  for (let i = 1; i < bars.length; i++) {
    const prev = bars[i - 1];
    const curr = bars[i];

    // Skip if MAs are not yet calculated
    if (prev.fast_ma === null || curr.slow_ma === null) {
      continue;
    }

    // Bullish crossover: fast MA crosses above slow MA
    const prevDiff = prev.fast_ma - prev.slow_ma;
    const currDiff = curr.fast_ma - curr.slow_ma;

    if (prevDiff <= 0 && currDiff > 0) {
      // BUY signal
      points.push({
        time: curr.time,
        type: "low",
        price: curr.low - 0.0005,
        label: "BUY",
        color: "#3b82f6",
        shape: "arrowUp",
        size: 2,
      });
    } else if (prevDiff >= 0 && currDiff < 0) {
      // SELL signal
      points.push({
        time: curr.time,
        type: "high",
        price: curr.high + 0.0005,
        label: "SELL",
        color: "#f97316",
        shape: "arrowDown",
        size: 2,
      });
    }
  }

  return points;
}

Step 6: Submit to InnovaTrading

def submit_indicator(points):
    """Submit indicator points to the API."""
    if not points:
        print("No signals to submit")
        return None

    url = f"{BASE_URL}/api/external/indicators/ma_crossover"
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }

    payload = {
        "symbol": SYMBOL,
        "timeframe": TIMEFRAME,
        "indicator_name": f"MA Crossover ({FAST_MA}/{SLOW_MA})",
        "version": "1.0",
        "points": points,
        "metadata": {
            "fast_period": FAST_MA,
            "slow_period": SLOW_MA,
            "total_signals": len(points)
        }
    }

    response = requests.post(url, json=payload, headers=headers)
    response.raise_for_status()
    return response.json()

async function submitIndicator(points) {
  if (points.length === 0) {
    console.log("No signals to submit");
    return null;
  }

  const url = `${config.BASE_URL}/api/external/indicators/ma_crossover`;

  const payload = {
    symbol: config.SYMBOL,
    timeframe: config.TIMEFRAME,
    indicator_name: `MA Crossover (${config.FAST_MA}/${config.SLOW_MA})`,
    version: "1.0",
    points,
    metadata: {
      fast_period: config.FAST_MA,
      slow_period: config.SLOW_MA,
      total_signals: points.length,
    },
  };

  const response = await axios.post(url, payload, {
    headers: {
      Authorization: `Bearer ${config.API_KEY}`,
      "Content-Type": "application/json",
    },
  });

  return response.data;
}

Step 7: Put It All Together

def main():
    print("=" * 50)
    print("MA Crossover Indicator")
    print("=" * 50)

    # 1. Fetch data
    print("\n1. Fetching market data...")
    bars = get_bars(500)
    print(f"   Fetched {len(bars)} bars")

    # 2. Calculate MAs
    print("\n2. Calculating moving averages...")
    bars = add_moving_averages(bars)

    # 3. Detect crossovers
    print("\n3. Detecting crossovers...")
    signals = detect_crossovers(bars)
    print(f"   Found {len(signals)} signals")

    if signals:
        print("\n   Recent signals:")
        for s in signals[-5:]:
            print(f"   - {s['label']} at {s['price']:.5f}")

    # 4. Submit to API
    print("\n4. Submitting to InnovaTrading...")
    result = submit_indicator(signals)

    if result:
        print(f"   Success! {result['points_received']} points submitted")
        print(f"   Expires at: {result['expires_at']}")
    else:
        print("   No signals to submit")

    print("\n" + "=" * 50)
    print("Done! Check your chart to see the signals.")
    print("=" * 50)

if __name__ == "__main__":
    main()

async function main() {
  console.log("=".repeat(50));
  console.log("MA Crossover Indicator");
  console.log("=".repeat(50));

  try {
    // 1. Fetch data
    console.log("\n1. Fetching market data...");
    let bars = await getBars(500);
    console.log(`   Fetched ${bars.length} bars`);

    // 2. Calculate MAs
    console.log("\n2. Calculating moving averages...");
    bars = addMovingAverages(bars);

    // 3. Detect crossovers
    console.log("\n3. Detecting crossovers...");
    const signals = detectCrossovers(bars);
    console.log(`   Found ${signals.length} signals`);

    if (signals.length > 0) {
      console.log("\n   Recent signals:");
      signals.slice(-5).forEach((s) => {
        console.log(`   - ${s.label} at ${s.price.toFixed(5)}`);
      });
    }

    // 4. Submit to API
    console.log("\n4. Submitting to InnovaTrading...");
    const result = await submitIndicator(signals);

    if (result) {
      console.log(`   Success! ${result.points_received} points submitted`);
      console.log(`   Expires at: ${result.expires_at}`);
    }

    console.log("\n" + "=".repeat(50));
    console.log("Done! Check your chart to see the signals.");
    console.log("=".repeat(50));
  } catch (error) {
    console.error("Error:", error.message);
  }
}

main();

Step 8: Run It!

python main.py
# or
node main.js

Expected output:

==================================================
MA Crossover Indicator
==================================================

1. Fetching market data...
   Fetched 500 bars

2. Calculating moving averages...

3. Detecting crossovers...
   Found 8 signals

   Recent signals:
   - BUY at 1.10250
   - SELL at 1.10450
   - BUY at 1.10300

4. Submitting to InnovaTrading...
   Success! 8 points submitted
   Expires at: 2025-12-13T14:00:00Z

==================================================
Done! Check your chart to see the signals.
==================================================

Step 9: View on Chart

Open InnovaTrading
Navigate to EURUSD H1 chart
Open the External Indicators panel
Your “MA Crossover” indicator should appear
Toggle it ON to see the signals

Next Steps

Add Stop Loss & Take Profit

Make your signals actionable with risk management levels

Continuous Updates

Set up automatic signal updates

Full Source Code

Download the complete example:

Get Started

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Core Concepts

Guides

Examples

Support

Prerequisites

What We’ll Build

Step 1: Set Up Your Project

Step 2: Create the Configuration

Step 3: Fetch Market Data

Step 4: Calculate Moving Averages

Step 5: Detect Crossovers

Step 6: Submit to InnovaTrading

Step 7: Put It All Together

Step 8: Run It!

Step 9: View on Chart

Next Steps

Add Stop Loss & Take Profit

Continuous Updates

Full Source Code

​Prerequisites

​What We’ll Build

​Step 1: Set Up Your Project

​Step 2: Create the Configuration

​Step 3: Fetch Market Data

​Step 4: Calculate Moving Averages

​Step 5: Detect Crossovers

​Step 6: Submit to InnovaTrading

​Step 7: Put It All Together

​Step 8: Run It!

​Step 9: View on Chart

​Next Steps

Add Stop Loss & Take Profit

Continuous Updates

​Full Source Code

Prerequisites

What We’ll Build

Step 1: Set Up Your Project

Step 2: Create the Configuration

Step 3: Fetch Market Data

Step 4: Calculate Moving Averages

Step 5: Detect Crossovers

Step 6: Submit to InnovaTrading

Step 7: Put It All Together

Step 8: Run It!

Step 9: View on Chart

Next Steps

Full Source Code