sector rotation for beginners

    by nowrich

    1

    A simplified sector rotation framework to identify and rank market-leading ETFs using relative strength and macro data.

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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'm looking at XLK, XLE, and XLV. Tech is above the 200-day but the ratio to SPY is flat. Energy is rising on high volume with oil prices up. Healthcare is below its 200-day. Rank these.

    Your agent does

    1. XLE (Score: 4) - Strong RS, macro tailwinds, confirmed breadth, persistent trend.
    2. XLK (Score: 2) - Trend is intact but losing relative momentum; macro context is mixed.
    3. XLV (Score: 0) - Avoid; price is below the 200-day moving average.

    Action: Rotate capital into XLE.

    What you get

    Rank industry sectors using a standardized 0-4 scorecard.Detect trend persistence using 50-day and 200-day moving average crossovers.Align portfolio allocations with Federal Reserve interest rate cycles.Validate sector breakouts using volume-based breadth proxies.

    About this skill

    The problem

    Identifying market leadership is difficult for non-institutional investors who lack expensive data terminals. Retail traders often entry sectors at their peak or hold laggards because they cannot quantify relative strength or macro alignment.

    What it does

    • Evaluates sector ETFs using price-to-market ratio charts to identify outperformance.
    • Synthesizes macro indicators like interest rates and inflation into actionable sector biases.
    • Filters noise using volume-based breadth checks and moving average persistence.
    • Generates a numerical scorecard to rank sectors for monthly or quarterly rotation.

    Why this beats prompting it yourself

    General LLMs often provide vague financial advice or hallucinate complex technical indicators. This skill enforces a specific, disciplined ranking framework that balances price action with fundamental macro logic, preventing emotional trading decisions.

    Use cases

    • Identify which equity sectors to overweight in a monthly portfolio rebalance.
    • Determine if a recent sector spike is supported by volume or is a bull trap.
    • Scan for sectors that remain resilient during broad market downturns.
    • Match current Federal Reserve policy to the most historically favorable industries.

    How to install

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

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