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Custom ORB Algo for MNQ Futures: Reddit Insights & Research Risks

#algo #pinescript #orb #mnq #futures #tradingview #backtesting #volatility
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General
November 18, 2025
Custom ORB Algo for MNQ Futures: Reddit Insights & Research Risks

Related Stocks

TSLA
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TSLA
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NVDA
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NVDA
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MNQ
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MNQ
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Reddit Factors

A Reddit user in r/FuturesTrading developed a customized opening range breakout (ORB) algorithm using Pine Script for MNQ Micro E-mini Nasdaq futures, reporting promising 1-year results with fills matching TradingView signals. Comments raised questions about testing across market regimes (e.g., 2020 COVID crash, 2022 bear market) and implementation details; the user plans to conduct regime testing and noted using YouTube and ChatGPT to build the script.

Research Findings
  • ORB strategies for futures are widely available on TradingView but are primarily educational tools with limited 2024-2025 quantitative performance data [3]. They excel in trending markets but face risks like overfitting and parameter instability [2].
  • TradingView’s backtesting for MNQ has critical limitations: perfect fill assumptions, no default slippage modeling, and execution delays that create gaps between backtest and live results [4]. MNQ’s tech-heavy composition (including TSLA and NVDA) adds volatility-related execution challenges [7].
Synthesis

The Reddit user’s promising results align with research indicating ORB strategies can perform well for MNQ in favorable regimes, but the lack of regime testing and TradingView’s backtesting flaws suggest live performance may differ. The user’s plan to test across regimes addresses a key risk identified in research.

Risks & Opportunities
  • Risks
    : Overfitting to historical data, unrealistic backtest assumptions, MNQ’s volatility impacting execution, and failure in non-trending regimes.
  • Opportunities
    : Integrating filters (e.g., MACD, RSI) to enhance signal quality [8,9], conducting regime testing, and manually configuring slippage/commissions in backtests to better reflect live conditions.
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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.