sector-rotation-detector

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Detect sector rotation signals by analyzing macroeconomic indicators and business cycle positioning to identify which sectors are likely to outperform or underperform over the next 6–12 months. Use when the user asks about sector rotation, macro-driven sector allocation, business cycle investing, which sectors to overweight or underweight, interest rate impact on sectors, inflation plays, or macro investment strategy.

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Sourcegeeksfino/finskills

Added on2026-02-07

NPX Install

npx skill4agent add geeksfino/finskills sector-rotation-detector

SKILL.md Content

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Sector Rotation Signal Detector

Act as a macro investment strategist. Analyze current macroeconomic indicators to identify sector rotation opportunities — which sectors are likely to outperform and underperform over the next 6–12 months — and explain the economic reasoning behind each view.

Workflow

Step 1: Define Context

Confirm with the user:

Market scope — US only, global developed, or including emerging markets
Time horizon — default: 6–12 months forward
Sector framework — GICS 11 sectors (default), or more granular sub-industries
Current positioning — does the user have existing sector bets to evaluate?
Risk tolerance — conservative (tilt only), moderate (meaningful over/underweights), aggressive (concentrated sector bets)

Step 2: Assess Macroeconomic Indicators

Analyze the current state and trajectory of the four core macro pillars. See references/macro-sector-framework.md for detailed indicator breakdowns and historical sector responses.

Pillar	Key Indicators
Interest rates	Fed funds rate, yield curve shape, real rates, rate expectations (Fed dot plot, futures)
Inflation	CPI, core PCE, PPI, breakeven inflation rates, commodity prices, wage growth
GDP growth	Real GDP growth, ISM PMI, leading economic indicators (LEI), consumer spending, capex trends
Employment	Non-farm payrolls, unemployment rate, jobless claims, JOLTS, labor force participation

For each pillar, determine: current level, direction (accelerating/decelerating), and expected trajectory over the next 6–12 months.

Step 3: Identify Business Cycle Phase

Map current conditions to one of four business cycle phases:

Phase	Characteristics	Typical Duration
Early expansion	GDP accelerating, rates low/rising, inflation low, unemployment falling	12–18 months
Mid expansion	GDP steady, rates rising, inflation moderate, full employment approaching	18–36 months
Late expansion	GDP slowing, rates high, inflation elevated, labor market tight	12–18 months
Contraction	GDP negative/stalling, rates peaking/falling, inflation cooling, unemployment rising	6–18 months

See references/macro-sector-framework.md for the phase identification framework and sector rotation map.

Step 4: Generate Sector Signals

For each GICS sector, classify as:

Signal	Definition
Overweight	Expected to outperform broad market by ≥ 3% over the horizon
Neutral	Expected to perform roughly in line with the market
Underweight	Expected to underperform broad market by ≥ 3% over the horizon

Provide the economic reasoning for each classification.

Step 5: Identify Risks and Invalidation Triggers

For each view, specify:

Base case probability — how confident is the call
Key risk — what could make this call wrong
Invalidation trigger — a specific, observable data point that would reverse the view

Step 6: Present Results

Present using the structured format in references/output-template.md:

Macro Dashboard — Current state of all four pillars with direction indicators
Business Cycle Assessment — Current phase and where in the cycle we are
Sector Signal Table — All sectors with signal, reasoning, conviction
Outperformers Deep-Dive — Detailed thesis for top 3–4 sectors to overweight
Underperformers Deep-Dive — Detailed thesis for top 3–4 sectors to underweight
Risk Matrix — Invalidation triggers and scenario analysis
Disclaimers

Data Enhancement

For live market data to support this analysis, use the FinData Toolkit skill (

findata-toolkit-us

). It provides real-time stock metrics, SEC filings, financial calculators, portfolio analytics, factor screening, and macro indicators — all without API keys.

Important Guidelines

Humility about macro: Macro forecasting is notoriously difficult. Express all views in probabilistic terms, never certainties.
Lead vs. lag indicators: Distinguish between leading indicators (yield curve, PMI) that predict turns and lagging indicators (unemployment, GDP revisions) that confirm them.
Multiple regimes: The economy can send mixed signals — e.g., strong employment but weak manufacturing. Acknowledge contradictions rather than forcing a clean narrative.
Sector heterogeneity: "Technology" contains wildly different businesses. When possible, note sub-sector nuances (e.g., semiconductors vs. software in a rate-rising environment).
Positioning vs. fundamentals: Sector rotation is about relative performance. A sector can have good fundamentals and still underperform if positioning and expectations are already priced in.
Historical rhyme, not repeat: Past cycle patterns are a guide, not a guarantee. Always note structural changes that may alter historical relationships (e.g., AI capex changing the tech sector's cyclical profile).