economic-calendar

> **Skill:** Economic Calendar | **Domain:** trading | **Category:** data | **Level:** beginner > **Tags:** `trading`, `data`, `calendar`, `news`, `high-impact`, `avoidance` # Economic Calendar ## High-Impact Events by Currency | Event | Currency | Frequency | Typical Impact | |-------|----------|-----------|----------------| | NFP (Non-Farm Payrolls) | USD | Monthly (1st Fri) | 50–150 pips | | FOMC Rate Decision | USD | 8x/year | 50–200 pips | | CPI (Inflation) | USD/EUR/GBP | Monthly | 30–100 pips | | GDP | USD/EUR/GBP | Quarterly | 20–80 pips | | PMI (Mfg/Services) | Multi | Monthly | 20–60 pips | | BoE/ECB/BoJ Decision | GBP/EUR/JPY | 8x/year | 50–150 pips | | EIA Oil Inventory | OIL | Weekly (Wed 14:30 UTC) | $0.50–2.00 | ## News Avoidance Windows ```python from datetime import datetime, timedelta def is_news_blackout(event_time: datetime, current_time: datetime, impact: str = "HIGH") -> bool: """Should we avoid trading near this news event?""" windows = {"HIGH": (30, 15), "MEDIUM": (15, 5), "LOW": (5, 0)} # (before_min, after_min) before, after = windows.get(impact, (30, 15)) start = event_time - timedelta(minutes=before) end = event_time + timedelta(minutes=after) return start <= current_time <= end def news_risk_level(minutes_to_event: float) -> str: if minutes_to_event < 5: return "EXTREME — do not trade" if minutes_to_event < 15: return "HIGH — reduce size 50%" if minutes_to_event < 30: return "ELEVATED — tight stops" return "NORMAL" ``` ## Fetch Calendar (Investing.com scrape) ```python import requests from bs4 import BeautifulSoup def get_todays_events(min_impact: str = "high") -> list: """Scrape Investing.com economic calendar for today's events.""" # Note: Use WebSearch tool to get current day's events # WebSearch query: f"site:investing.com economic calendar today {min_impact} impact" pass # Alternative: use Brave Search via WebSearch tool CALENDAR_QUERY = "economic calendar high impact events today forex" ``` ## Pre-Event Volatility Strategy - **30 min before high-impact**: Spreads widen, stops get hunted — close scalps - **Straddle setup**: Place buy stop + sell stop at current price ±(avg_range/3) before NFP - **Post-event fade**: If spike > 2× ATR, fade back within 5–15 min (70% fill rate) ## Key UTC Times (Daily Schedule) ```python DAILY_EVENTS = { "00:30": "AUD data (RBA related)", "07:00": "EUR data + London open", "09:30": "GBP data", "12:30": "USD major data (CPI, NFP, retail)", "13:30": "NYSE open — US equity data", "14:30": "EIA oil inventory (Wednesday only)", "18:00": "FOMC (when scheduled)", "22:00": "NZD/AUD data + NY close", } ``` --- ## Related Skills - [Market Intelligence](../market-intelligence.md) - [News Data Stream](../news-intelligence.md) - [Strategy Selection](../strategy-selection.md)