Forex strategy guides

Scalping is a high-frequency trading strategy that captures small pip movements (3-15 pips per trade) on short timeframes (M1-M5), typically holding positions for seconds to minutes. The strategy depends heavily on tight spreads, fast execution, and high win rates (60-80% typical) with small reward-to-risk ratios (0.5-1.5). Net profitability depends more on broker quality and execution friction than on signal logic — a marginal-edge scalper on an ECN broker can be profitable while a strong-edge scalper on a market-maker broker is not.

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Breakout trading captures the directional move that follows a period of price consolidation. The strategy identifies a defined price range (typically the Asian-session range or pre-London consolidation), waits for price to close decisively beyond the range, and enters in the direction of the break. Win rates are moderate (40-55%) with favourable reward-to-risk ratios (1.5-2.5:1). The strategy works well during high-volume session opens (London 08:00 UTC, New York 13:00 UTC) and fails in low-volatility regimes when ranges are not followed by directional moves.

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Trend-following captures sustained directional moves by entering in the direction of an established trend and holding through pullbacks until the trend ends. The strategy typically uses H4 or D1 timeframes with 30-45% win rate and 2.5-4:1 reward-to-risk ratios — fewer winners but each winner much larger than each loser. Long-run profitability is excellent across decades of academic data, but the strategy suffers significant drawdowns in ranging regimes (sometimes 6-12 months of underperformance). Patience and capital preservation discipline are the operational requirements.

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Gold (XAUUSD) is the highest-volatility 'major' instrument retail traders access. Daily ranges of 100-300 points are normal; news days exceed 500. The trading approaches that work on FX majors (scalping, breakout, trend) all apply to gold but with adjusted parameters: wider stops, smaller position sizes per dollar of equity, and stricter news filters because gold spread widening during news is more dramatic. The opportunity is real (gold trends powerfully) but the risk-adjusted edge requires gold-specific tuning, not just running general-purpose EAs on the gold symbol.

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Mean reversion trades the assumption that price extremes (overbought / oversold) tend to revert toward an average. The strategy enters counter-direction at extreme readings (e.g. RSI < 30 = buy, RSI > 70 = sell) and exits at the mean or moderate level. Win rates are high (60-75%) with small reward-to-risk ratios (0.7-1.5:1). The strategy is the dominant winning approach in ranging regimes (40-60% of the time historically) and the dominant losing approach in trending regimes — combining mean-reversion with trend-following in a portfolio smooths returns across regime cycles.

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Swing trading targets multi-day moves on H4 or D1 timeframes, typically holding positions 2-10 days. Entry signals combine trend identification with pullback patterns; exits use wide trailing stops or fixed take-profits at multi-day swing levels. Win rates 40-55%, R:R 2:1 to 3:1, low trade frequency (1-5 per week per pair). Swing trading is less operationally demanding than scalping but requires patience for setups and tolerance for multi-day drawdown variance. Swap costs become material on multi-day holds.

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Hedging in forex means holding both long and short positions on the same currency pair simultaneously, typically to manage existing exposure or earn carry. MT5 supports hedging on most retail brokers; CFTC-regulated US brokers force netting accounts where hedging is mechanically impossible. Hedging adds value in specific cases (managing existing position risk, earning carry-trade interest differentials, prop firm rule satisfaction) but is often misused as a way to postpone realising losses — which has tax implications and rarely produces better outcomes than simply closing the original losing position.

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News trading targets the directional move that follows major economic releases (NFP, FOMC rate decisions, CPI, central bank statements). The strategy enters during or immediately after the release to capture the rapid price movement. Win rates can exceed 60% but the spread widening during news events (5-20× normal) creates execution friction that destroys most retail news strategies. Profitable news trading requires institutional-grade execution (sub-50ms latency, raw spreads, no broker-side execution restrictions) that few retail traders have. Most retail traders are better-served by filtering OUT news events than by attempting to trade them.

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Grid trading places a layered series of buy and sell orders at fixed price intervals around a starting price, accumulating profit as price oscillates and using new layers to average down on losing positions. The math works in ranging markets but fails catastrophically in strong directional moves. Grid EAs have notoriously misleading backtests because survivor-bias hides accounts that blew up. FxRobotEasy does not implement grid strategies in production EAs — every EA we ship uses fixed stops and accepts losses cleanly rather than averaging down.

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Martingale doubles position size after each loss to recover with one winning trade. The math: a single winning trade after N consecutive losses recovers all prior losses plus the original target profit. The risk: N consecutive losses is rare but inevitable given enough time, and exponentially-doubling positions hit broker margin limits or account-zero before recovery. Backtests showing 'consistent profits' from martingale almost always either survived a lucky period or used unbounded position sizing that no real account can sustain. FxRobotEasy explicitly excludes martingale from production EAs.

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Dollar-cost averaging (DCA) is the practice of buying a fixed dollar amount of an asset at regular intervals regardless of price, on the thesis that long-run trend is upward. DCA works well on assets with secular upward drift (broad equity indices, well-validated crypto over multi-decade periods). DCA fails in forex because currency pairs are structurally mean-reverting over multi-year horizons — there is no long-run upward drift to amortise against. Applying crypto-DCA mental models to forex produces predictable underperformance.

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ICT / Smart Money Concepts (SMC) is a technical analysis framework focused on identifying institutional buy/sell zones through specific price-action patterns: order blocks, fair value gaps, liquidity sweeps, breaker blocks, and displacement. Automation is partial — pattern detection is codable, but the multi-timeframe contextual interpretation that drives manual ICT trading is harder to systematise. This page provides a concise overview; the full deep-dive lives in our Stage 09 ICT cluster covering 6 glossary terms and a dedicated how-to automation guide.

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AI / machine learning in forex EAs typically means: (1) feature engineering on price + indicator data, (2) supervised learning models (gradient boosting, neural networks) trained to predict short-term direction or volatility, (3) periodic retraining on rolling windows of recent data. Realistic results: well-engineered ML EAs can add 10-30% net profit factor improvement over rules-based strategies on the same setups. Marketing claims of 'AI revolutionising forex' substantially overstate what ML practically achieves; the real edge is modest improvement, not transformative breakthrough.

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Forex arbitrage refers to trading strategies that exploit price differences between related instruments or markets. Two main categories: (1) Latency arbitrage — exploiting micro-second price differences between brokers / exchanges, requires institutional infrastructure (co-located servers, sub-millisecond latency). (2) Statistical arbitrage — modeling pricing relationships between correlated instruments and trading divergences from the model. Both are institutionally dominant; retail-marketed 'arbitrage' EAs almost never do actual arbitrage. They use the term as marketing for unrelated strategies. Honest disclosure: retail traders cannot realistically execute true forex arbitrage.

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