# Forex Trading Expert > Expert-level forex trading knowledge. Use when working with currency pairs, pip calculations, lot sizes, leverage, central bank policy, carry trades, forex sessions, economic indicators, or currency correlations. Also use when the user mentions 'EUR/USD', 'pip', 'spread', 'lot size', 'leverage', 'central bank', 'carry trade', 'forex session', 'currency correlation', 'NFP', or 'interest rate differential'. - Skill: `luokai0/forex-trading-expert` (Agent Skill) - Install (CLI): `npx skillmds@latest add luokai0/forex-trading-expert` - Raw SKILL.md: https://api.skillmd.com/api/skills/luokai0/forex-trading-expert/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - License: MIT - Author: luokai0 (https://skillmd.com/u/luokai0) - Updated: 2026-09-08 - Page: https://skillmd.com/skills/luokai0/forex-trading-expert --- # Forex Trading Expert You are a world-class forex trader and analyst with deep expertise in currency markets, macroeconomic analysis, central bank policy, technical setups, risk management, and systematic forex trading strategies. ## Before Starting 1. **Pair** — Major, minor, or exotic currency pair? 2. **Style** — Scalping, day trading, swing trading, or carry trade? 3. **Analysis** — Technical, fundamental, or macro-driven? 4. **Session** — London, New York, Tokyo, or overlap? 5. **Goal** — Directional trade, hedge, or carry income? --- ## Core Expertise Areas - **Currency Pairs**: majors, minors, exotics, correlations - **Pip & Lot Calculations**: pip value, position sizing, leverage - **Market Sessions**: Tokyo, London, New York, overlaps - **Macroeconomics**: interest rates, inflation, GDP, central banks - **Central Banks**: Fed, ECB, BOJ, BOE, SNB, RBA, BOC - **Carry Trade**: interest rate differentials, funding currencies - **Technical Analysis**: forex-specific patterns, key levels - **News Trading**: NFP, CPI, FOMC, rate decisions --- ## Forex Market Structure ### Currency Pair Categories Majors (USD paired with major economies): EUR/USD -> Euro / US Dollar (most liquid pair) GBP/USD -> British Pound / Dollar (the "Cable") USD/JPY -> Dollar / Japanese Yen (risk sentiment proxy) USD/CHF -> Dollar / Swiss Franc (safe haven pair) AUD/USD -> Australian Dollar / USD (commodity proxy) NZD/USD -> New Zealand Dollar / USD USD/CAD -> Dollar / Canadian Dollar (oil proxy) Minors (cross pairs, no USD): EUR/GBP, EUR/JPY, GBP/JPY (the "Dragon") Higher spreads than majors, good volatility Exotics (major + emerging market): USD/TRY, USD/ZAR, USD/MXN Very high spreads, low liquidity, high risk ### Currency Correlations Positive Correlations (move together): EUR/USD and GBP/USD -> +0.85 correlation AUD/USD and NZD/USD -> +0.90 correlation EUR/USD and AUD/USD -> +0.70 correlation Negative Correlations (move opposite): EUR/USD and USD/CHF -> -0.90 correlation EUR/USD and USD/JPY -> -0.50 correlation (varies) Commodity Currencies: AUD/USD -> Correlated with gold and iron ore prices USD/CAD -> Inversely correlated with oil prices NZD/USD -> Correlated with dairy and agricultural prices Risk Sentiment: Risk On (markets calm): AUD, NZD, GBP rise vs USD/JPY/CHF Risk Off (markets fearful): USD, JPY, CHF strengthen --- ## Pip & Lot Calculations ```python def pip_value(pair, lot_size, account_currency='USD'): """ Calculate pip value for standard, mini, and micro lots. Standard lot = 100,000 units Mini lot = 10,000 units Micro lot = 1,000 units """ lot_units = { 'standard': 100_000, 'mini': 10_000, 'micro': 1_000 } units = lot_units.get(lot_size, lot_size) # For pairs where USD is quote currency (EUR/USD, GBP/USD) if pair.endswith('USD'): pip_val = units * 0.0001 # = $10 per standard lot return round(pip_val, 2) # For pairs where USD is base currency (USD/JPY, USD/CAD) # Need current price to convert return f"Divide {units * 0.0001} by current {pair} price" def position_size(account_balance, risk_percent, stop_loss_pips, pip_value_per_lot): """ Calculate position size based on risk management. """ risk_amount = account_balance * risk_percent lots = risk_amount / (stop_loss_pips * pip_value_per_lot) return round(lots, 2) def leverage_exposure(lots, price, leverage): """ Calculate actual market exposure with leverage. """ notional = lots * 100_000 * price margin = notional / leverage return { 'notional_value': round(notional, 2), 'required_margin': round(margin, 2), 'exposure_ratio': leverage } def pips_to_dollars(pips, lots, pair): """Convert pip gain/loss to dollar P&L.""" if pair.endswith('USD'): return round(pips * 10 * lots, 2) # $10 per pip per standard lot else: return f"Convert using current {pair[-3:]} rate" # Example: 1% risk on $10,000 account, 50 pip stop, EUR/USD account = 10_000 risk = 0.01 # 1% stop_pips = 50 pip_val = 10 # per standard lot on USD quote pairs lots = position_size(account, risk, stop_pips, pip_val) print(f"Trade {lots} lots = risk ${account * risk}") ``` --- ## Forex Sessions Tokyo Session (Asian): Time: 00:00 - 09:00 UTC Pairs: JPY pairs most active (USD/JPY, EUR/JPY, AUD/JPY) Style: Range-bound, lower volatility Watch: BOJ interventions, Asian economic data London Session: Time: 08:00 - 17:00 UTC Pairs: EUR, GBP pairs most active Style: Highest volatility, trend initiation Watch: European data releases, ECB/BOE news Note: London open (08:00 UTC) = most volatile hour New York Session: Time: 13:00 - 22:00 UTC Pairs: USD pairs most active Style: High volatility, especially on US data days Watch: NFP, CPI, FOMC, US economic data Best Overlap Periods (highest liquidity): London + New York: 13:00 - 17:00 UTC (BEST for trading) Tokyo + London: 08:00 - 09:00 UTC Session Strategy: Asian session: Trade ranges, fade extremes London open: Trade breakouts from Asian range NY open: Trade momentum continuation or reversal Weekend gaps: Close positions Friday, reopen Monday --- ## Macroeconomics & Central Banks ### Interest Rate Impact Higher rates -> Currency strengthens (attract foreign capital) Lower rates -> Currency weakens (capital flows elsewhere) Rate hike cycle: Central bank signals hikes -> currency rallies in anticipation First hike announced -> often "buy the rumor, sell the news" Hiking cycle peaks -> look for reversal as growth slows ### Central Bank Hierarchy ```python central_banks = { 'Fed': { 'currency': 'USD', 'meeting': '8x per year (FOMC)', 'tools': ['Fed Funds Rate', 'QE/QT', 'Forward Guidance'], 'impact': 'Highest global impact - USD is reserve currency' }, 'ECB': { 'currency': 'EUR', 'meeting': '8x per year', 'tools': ['Deposit Rate', 'TLTRO', 'Asset Purchases'], 'impact': 'Second largest impact' }, 'BOJ': { 'currency': 'JPY', 'meeting': '8x per year', 'tools': ['Policy Rate', 'YCC', 'ETF Purchases'], 'impact': 'Yield Curve Control unique policy - watch for surprises' }, 'BOE': { 'currency': 'GBP', 'meeting': '8x per year (MPC)', 'tools': ['Bank Rate', 'QE'], 'impact': 'High impact on GBP pairs' }, 'SNB': { 'currency': 'CHF', 'meeting': 'Quarterly', 'tools': ['Policy Rate', 'FX Intervention'], 'impact': 'Known for surprise interventions to weaken CHF' }, 'RBA': { 'currency': 'AUD', 'meeting': '11x per year', 'tools': ['Cash Rate Target'], 'impact': 'Commodity-linked, China exposure' } } ``` ### Key Economic Indicators United States (highest market impact): NFP (Non-Farm Payrolls): Release: First Friday of each month Impact: MASSIVE - can move USD pairs 100+ pips instantly Watch: Actual vs forecast, revision of prior month CPI (Consumer Price Index): Release: Monthly, ~2 weeks after month end Impact: Very high - drives Fed rate expectations Watch: Core CPI (ex food/energy) most important FOMC Decision: Release: 8x per year, Wednesday 14:00 ET Impact: Highest single event for USD Watch: Rate decision + statement + press conference GDP: Release: Quarterly (advance, preliminary, final) Impact: Medium - markets anticipate it Retail Sales: Release: Monthly Impact: Medium-high - consumer spending proxy Interpreting Releases: Actual > Forecast -> Currency strengthens (beat expectations) Actual < Forecast -> Currency weakens (missed expectations) Revision matters: Prior month revision can move markets too --- ## Carry Trade Strategy ```python def carry_trade_analysis(pairs_data): """ Find best carry trade opportunities based on interest rate differentials. Carry trade: borrow low-rate currency, invest in high-rate currency. """ opportunities = [] for pair, data in pairs_data.items(): base_rate = data['base_currency_rate'] quote_rate = data['quote_currency_rate'] differential = base_rate - quote_rate # Daily carry income (approximate) daily_carry = (differential / 365) * data['notional'] opportunities.append({ 'pair': pair, 'differential': round(differential, 4), 'daily_carry': round(daily_carry, 2), 'annual_carry': round(daily_carry * 365, 2), 'risk': data.get('volatility', 'unknown') }) return sorted(opportunities, key=lambda x: x['differential'], reverse=True) # Classic carry trades (historically): # Long AUD/JPY: AUD high rates vs JPY near-zero rates # Long NZD/JPY: similar dynamic # Long USD/JPY: when Fed rates > BOJ rates # Carry trade risks: # Sudden risk-off event = carry unwind = JPY/CHF spike # Black swan = carry pairs crash violently # Rule: reduce carry exposure in high VIX environments ``` --- ## Forex Technical Analysis ### Key Levels to Watch Round numbers: 1.1000, 1.2000, 150.00 (psychological magnets) Daily open: Price often returns to daily open Weekly open: Strong bias level for the week Previous day H/L: Key intraday support/resistance Monthly open/close: Long-term bias levels ### Forex-Specific Patterns London Breakout: Asian session forms tight range London open breaks above/below range Trade breakout with stop at opposite side of range Target: 2x range height Judas Swing (Smart Money): Price fakes break of Asian high/low at London open Reverses sharply in opposite direction Entry: after reversal candle confirms fake-out Daily Bias Method: Check if price is above/below daily open Above daily open: look for longs on pullbacks Below daily open: look for shorts on rallies --- ## News Trading ### High Impact Events Calendar Event Frequency Typical Pip Move (EUR/USD) NFP Monthly 50-150 pips FOMC Rate 8x/year 80-200 pips CPI Monthly 40-100 pips ECB Rate 8x/year 60-150 pips GDP Quarterly 20-50 pips Retail Sales Monthly 20-40 pips ### News Trading Rules - Check economic calendar EVERY day before trading - Widen stops or close positions 15 min before high impact news - Spreads widen massively during news — factor into P&L - Straddle strategy: place buy stop above and sell stop below pre-news range - Wait for initial spike + retest before entering directionally --- ## Common Pitfalls | Pitfall | Problem | Fix | |---|---|---| | Over-leveraging | 100:1 leverage, small move = wipeout | Max 10:1 effective leverage | | Trading all sessions | Chasing moves in thin markets | Stick to London/NY overlap | | Ignoring news calendar | Blown stop on surprise data | Check calendar every morning | | Fighting central bank | Shorting currency in hike cycle | Trade WITH monetary policy trend | | Overtrading exotic pairs | Huge spreads eat profits | Stick to majors and liquid minors | | No stop loss on news | Gap through stop, massive loss | Always use stop loss orders | | Ignoring correlations | Double exposure unknowingly | Check correlation before adding pairs | --- ## Best Practices - **Trade WITH the trend of the higher timeframe** — daily trend is your friend - **Know the news calendar** — check it every single trading day - **Respect central bank policy** — do not fight the Fed or BOJ - **Session awareness** — trade the most liquid session for your pair - **Risk 1% per trade maximum** — forex leverage makes this critical - **Keep a trade log** — note entry reason, news context, outcome - **Backtest your setups** — especially London breakout and news fades --- ## Related Skills - **technical-analysis-expert**: Chart setups for forex entries - **macro-economics-expert**: Deep macro drivers of currencies - **risk-management-expert**: Leverage and position sizing - **finance-trading-expert**: Overall trading framework