Strategy Classes

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Overview

Every strategy in ForgeAI belongs to one of six classes. A class describes the primary analytical approach the strategy uses — not the user’s level or progression. When browsing the strategy library, you can filter by class to find strategies that match your preferred trading style or the market conditions you expect during a tournament.

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The Six Classes

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Fighter

Primary approach: Technical Analysis Fighter strategies analyze price charts, technical indicators, and historical price patterns to identify trade opportunities. Common signals include trend direction, momentum indicators (RSI, MACD), moving averages, and classic chart patterns. Typical market fit: Trending markets with clear directional movement and defined support/resistance levels. Example strategy categories: trend-following, breakout, momentum, swing

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Ranger

Primary approach: Social Sentiment Analysis Ranger strategies track social media activity, news feeds, community discussion, and crowd sentiment to anticipate price moves before they fully materialize in the chart. These strategies are reactive to narrative shifts. Typical market fit: Volatile, news-driven, or meme-driven markets where sentiment often leads price. Example strategy categories: sentiment, momentum

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Mage

Primary approach: On-Chain Analysis Mage strategies read raw blockchain data — wallet flows, DEX volume, whale accumulation/distribution, token unlocks, and on-chain metrics — to infer where smart money is moving. Typical market fit: Markets with high on-chain activity or where fundamental on-chain signals are a better leading indicator than price action alone. Example strategy categories: arbitrage, trend-following, custom

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Defender

Primary approach: Capital Preservation Defender strategies prioritize low drawdown and stable returns over maximum upside. They use hedging, conservative position sizing, and strict stop-losses. These strategies are designed to survive volatile periods with minimal losses. Typical market fit: Bear markets, high-uncertainty environments, or tournaments scored on risk-adjusted returns. Example strategy categories: mean_reversion, swing

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Gambler

Primary approach: High-Risk / High-Reward Gambler strategies concentrate on high-conviction momentum bursts, aggressive position sizing, and rapid entries. They accept large drawdowns in exchange for outsized upside. In strong trending conditions these strategies can dominate leaderboards. Typical market fit: Strong trending or breakout markets where conviction plays outperform steady diversification. Example strategy categories: scalping, breakout, momentum

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Rogue

Primary approach: Contrarian / Mean Reversion Rogue strategies fade crowd behavior — they buy when most are selling and sell when most are buying, betting on mean reversion. These strategies thrive when the market overreacts to news or when extreme sentiment readings signal exhaustion. Typical market fit: Range-bound or overextended markets where the crowd is leaning too hard in one direction. Example strategy categories: mean_reversion, sentiment, custom

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Class Comparison

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Next Steps