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Maple Research's public knowledge base: what Maple is, how it works, its research methodology, and a glossary of quantitative trading terms.

  • About Maple Research

    Maple Research is a quantitative research platform that helps traders test, validate, and understand trading strategies using historical data, statistical analysis, and AI-assisted research tools.

  • Our Mission

    Maple Research's mission is to make rigorous, evidence-based strategy testing accessible, replacing hype and hindsight bias with statistical discipline.

  • How Maple Works

    An overview of how Maple Research works: describe a strategy idea, backtest it against historical data, and run it through a series of statistical validation checks before drawing conclusions.

  • Features

    An overview of Maple Research's core features: AI-assisted strategy research, backtesting, robustness validation, a strategy library, paper trading, and market observation tools.

  • Technology

    Maple Research runs on a browser-based deterministic backtesting engine, secure server-side data proxying, and optional local AI assistance — no proprietary trading infrastructure or hidden black-box models.

  • Methodology

    Maple Research's validation methodology: out-of-sample testing, parameter sensitivity, sample-size checks, drawdown analysis, Monte Carlo simulation, walk-forward testing, and market-regime analysis.

  • Frequently Asked Questions

    Frequently asked questions about Maple Research: what it is, whether it gives financial advice, how backtesting works, and what data and technology it uses.

  • Roadmap

    The general direction of Maple Research's development: deeper strategy validation, an expanded research library, and continued focus on evidence-based, non-promotional research tools.

  • Philosophy

    Maple Research's philosophy: evidence over excitement, robustness over perfect backtests, and better questions over easy answers.

  • Security

    How Maple Research handles security: row-level data isolation, no client-side exposure of third-party API keys, and no brokerage or real-money trading connectivity.

  • Privacy

    How Maple Research handles user data: what is collected for signed-in accounts, what stays local in guest mode, and what third parties are involved.

  • Glossary of Quantitative Trading Terms

    A glossary of quantitative trading and strategy-validation terms — backtesting, overfitting, walk-forward testing, Monte Carlo simulation, drawdown, and more — as used in Maple Research.