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Mean-Reversion Equity Trader (Remote, Funded) Long Beach, CA

  2026-05-19     Maverick Trading     Long Beach,CA  
Description:

A mean-reversion equity trader at Maverick takes positions against short-term extremes in US equities — buying oversold conditions, selling overbought conditions, and holding for a return to a defined statistical mean. The strategy is most profitable in range-bound markets and gets punished in strong trends, which means a mean-reversion trader has to be honest about the market regime and willing to size down (or stand aside) when conditions don't favor the approach.Long Beach, CA:Long Beach is part of the broader LA metro and home to the Port of Long Beach (one of the busiest in the country), a meaningful aerospace industry, and a growing tech sector. Pacific Time means a 6:30am market open.What you'll trade:US equities and ETFs with sufficient liquidity, focusing on names where statistical mean-reversion has historical evidence. Most positions are short-term (3–10 trading days). Some variants of the strategy use options structures to define risk and benefit from IV mean reversion alongside price mean reversion.Risk framework:Mean reversion's worst losses come during regime changes — when a market shifts from range-bound to trending and the oversold names keep getting more oversold. Maverick traders cap exposure during such regimes and pay attention to broad-market trend indicators as a context filter, not just individual signals.Why Maverick funds this role:Mean reversion is one of the most studied and best-documented short-term equity strategies. Maverick funds it because the strategy is rule-based, scalable across names, and produces a P&L pattern that diversifies from momentum and trend-following.Traders who can stand aside during trending markets without forcing tradesPeople who think in expectancy and sample size, not single tradesCandidates with experience cutting losers fast — mean reversion loses worst when you average inTraders who understand that win rate alone is meaningless without the loss size to balance it#J-18808-Ljbffr


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