forex pair selection coach

    1

    A structured framework for selecting forex pairs based on liquidity, volatility, and session overlaps.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    I trade the London/NY overlap and want moderate volatility. I'm currently looking at EUR/USD, GBP/USD, and USD/JPY. Check these for correlations and events.

    Your agent does

    Watchlist Analysis: 1. Session: All three align with London/NY. 2. Correlation: EUR/USD and GBP/USD have high positive correlation. Keep EUR/USD; remove GBP/USD to avoid double exposure. 3. Volatility: All moderate. Final Watchlist: EUR/USD and USD/JPY. Note: Check for US CPI at 13:30 GMT.

    What you get

    Build a daily watchlist of high-liquidity currency pairs.Identify and remove highly correlated pairs to manage risk.Match currency selection to specific trading session overlaps.Avoid high-impact news events that cause unpredictable slippage.

    About this skill

    The problem

    Beginner traders often lose capital by overtrading exotic pairs or entering positions during low-liquidity hours. Without a structured selection process, they face unpredictable slippage, high spreads, and unintended risk amplification through correlated assets.

    What it does

    • Evaluates currency pairs against six core metrics: liquidity, spread, session overlap, volatility, correlation, and event exposure.
    • Filters out high-cost exotic pairs to prioritize major pairs with tighter spreads and reliable patterns.
    • Matches pair volatility and session activity to your specific trading schedule and risk tolerance.
    • Identifies positive and negative correlations to prevent accidental doubling of market exposure.
    • Cross-references economic calendars to avoid high-impact news events that trigger stop-losses.

    Why this beats prompting it yourself

    Generic prompts often fail to account for the technical relationship between session overlaps and liquidity. This skill applies a specific 8-step filtering sequence that mirrors professional risk management workflows, ensuring you don't just get a list of pairs, but a data-driven watchlist tailored to your local timezone.

    Use cases

    • Building a focused daily watchlist of 3-5 pairs based on current market sessions.
    • Auditing an existing portfolio to remove highly correlated positions that increase risk.
    • Selecting optimal pairs for a specific trading window, such as the London/New York overlap.
    • Filtering out pairs with imminent high-impact economic news releases like CPI or NFP.

    Known limitations

    Requires the user to provide current economic calendar data or ATR values for real-time filtering. Does not provide entry/exit signals or specific price targets.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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