Economic Calendar Trading: How to Automate News-Based Strategies

import requests
from datetime import datetime, timedelta

API_KEY = "your_api_key_here"
BASE_URL = "https://tickatlas.com/v1"
HEADERS = {"X-API-Key": API_KEY}

def get_upcoming_events(hours_ahead: int = 24) -> list[dict]:
    """Fetch economic events in the next N hours."""
    resp = requests.get(f"{BASE_URL}/calendar", params={
        "from": datetime.utcnow().isoformat(),
        "to": (datetime.utcnow() + timedelta(hours=hours_ahead)).isoformat()
    }, headers=HEADERS)
    return resp.json()["data"]["events"]

events = get_upcoming_events(24)
for event in events:
    print(f"{event['time']} | {event['currency']} | "
          f"{event['impact']} | {event['title']}")

// GET /v1/calendar?from=2026-03-28T00:00:00Z&to=2026-03-29T00:00:00Z&offset=0&limit=100
{
  "success": true,
  "data": {
    "events": [
      {
        "time": "2026-03-28T12:30:00Z",
        "currency": "USD",
        "impact": "high",
        "title": "Non-Farm Payrolls",
        "forecast": "180K",
        "previous": "175K"
      },
      {
        "time": "2026-03-28T12:30:00Z",
        "currency": "USD",
        "impact": "high",
        "title": "Unemployment Rate",
        "forecast": "3.8%",
        "previous": "3.9%"
      },
      {
        "time": "2026-03-28T09:00:00Z",
        "currency": "EUR",
        "impact": "medium",
        "title": "CPI Flash Estimate",
        "forecast": "2.4%",
        "previous": "2.6%"
      }
    ],
    "pagination": {
      "offset": 0,
      "limit": 100,
      "total": 3,
      "has_more": false
    }
  }
}

def is_safe_to_trade(symbol: str, buffer_minutes: int = 30) -> bool:
    """Check if any high-impact events are near for this symbol's currencies."""
    # Extract currencies from pair (e.g., EURUSD -> EUR, USD)
    base = symbol[:3]
    quote = symbol[3:]

    events = get_upcoming_events(hours_ahead=1)
    now = datetime.utcnow()

    for event in events:
        if event["impact"] != "high":
            continue
        if event["currency"] not in (base, quote):
            continue

        event_time = datetime.fromisoformat(event["time"].replace("Z", ""))
        minutes_until = (event_time - now).total_seconds() / 60

        # Too close to a high-impact event
        if -15 < minutes_until < buffer_minutes:
            print(f"Avoiding {symbol}: {event['title']} in {minutes_until:.0f}min")
            return False

    return True

# Usage in your trading bot
for pair in ["EURUSD", "GBPUSD", "USDJPY"]:
    if is_safe_to_trade(pair):
        # ... run your normal strategy
        pass
    else:
        print(f"Skipping {pair} — news event approaching")

def pre_news_analysis(symbol: str) -> dict:
    """Analyze technicals before an upcoming news event."""
    # Fetch current indicators
    ind_resp = requests.get(f"{BASE_URL}/indicators", params={
        "symbol": symbol,
        "timeframe": "H1",
        "indicators": "RSI_14,BBANDS_20,ATR_14"
    }, headers=HEADERS)
    indicators = ind_resp.json()["data"]["indicators"]

    rsi = indicators["RSI_14"]["value"]
    bb = indicators["BBANDS_20"]
    atr = indicators["ATR_14"]["value"]

    return {
        "symbol": symbol,
        "rsi": rsi,
        "rsi_zone": "oversold" if rsi < 30 else "overbought" if rsi > 70 else "neutral",
        "bb_position": "lower" if ind_resp.json()["data"]["price"]["close"] < bb["lower"] else
                       "upper" if ind_resp.json()["data"]["price"]["close"] > bb["upper"] else "middle",
        "expected_move": atr * 2,  # News events often produce 2x ATR moves
    }

def post_news_momentum(symbol: str) -> str:
    """Check for post-news momentum after a high-impact event."""
    resp = requests.get(f"{BASE_URL}/indicators", params={
        "symbol": symbol,
        "timeframe": "M15",  # Use short timeframe for post-news
        "indicators": "RSI_14,MACD,ADX_14"
    }, headers=HEADERS)

    data = resp.json()["data"]["indicators"]
    rsi = data["RSI_14"]["value"]
    macd_hist = data["MACD"]["histogram"]
    adx = data["ADX_14"]["value"]

    # Strong post-news trend: high ADX + aligned RSI and MACD
    if adx > 30:
        if macd_hist > 0 and rsi > 55:
            return "BUY — strong post-news bullish momentum"
        elif macd_hist < 0 and rsi < 45:
            return "SELL — strong post-news bearish momentum"

    return "WAIT — momentum not confirmed yet"