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Analyzing Business Cycle Positioning

ASecurity

Structures business cycle analysis with phase identification, leading indicator tracking, and sector implications. Use when identifying cycle phase, tracking business cycles, or assessing cyclical positioning.

22 stars
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Added 9/20/2026
businessgotesting

Works with

cli

Security Analysis

A100/100

Scanned 9/20/2026

Install to Claude Code

$npx -y skills add lev-os/agents --skill analyzing-business-cycle-positioning --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: analyzing-business-cycle-positioning
description: Structures business cycle analysis with phase identification, leading indicator tracking, and sector implications. Use when identifying cycle phase, tracking business cycles, or assessing cyclical positioning.
tags:
  - analysis
  - economic-analysis
metadata:
  author: casemark
  practice_areas:
    - Economic Research
    - Macroeconomics
    - Policy Analysis
  document_types:
    - Analysis Report
  skill_modes:
    - Analysis
---
# Analyzing Business Cycle Positioning

## When To Use

- Determining which phase of the business cycle an economy currently occupies (expansion, peak, contraction, trough)
- Assessing whether leading indicators signal a regime change or phase transition
- Positioning sector allocations, credit exposure, or policy recommendations relative to the cycle
- Evaluating the macro backdrop for investment committees, research notes, or policy briefings
- Stress-testing portfolio assumptions against cyclical turning points

## Inputs To Gather

- **GDP data**: Real GDP growth (quarter-over-quarter annualized, year-over-year), output gap estimates
- **Labor market**: Nonfarm payrolls trend, unemployment rate, initial jobless claims (4-week moving average), job openings-to-unemployed ratio
- **Leading indicators**: Conference Board Leading Economic Index (LEI), OECD Composite Leading Indicators, yield curve slope (10Y–2Y, 10Y–3M), ISM New Orders minus Inventories spread
- **Credit conditions**: Senior Loan Officer Opinion Survey (SLOOS), high-yield credit spreads, bank lending standards
- **Inflation & monetary policy**: Core PCE/CPI trajectory, Fed funds rate vs. neutral rate estimate, real interest rates
- **Corporate & consumer**: Earnings revision breadth, CEO confidence surveys, consumer sentiment (Michigan/Conference Board), retail sales trend
- **Time horizon**: Whether analysis targets the current quarter, 6-month forward, or full-cycle view
- **Geographic scope**: Single-country, regional bloc, or global synchronization assessment

## Workflow

1. **Classify the current phase**
   - Map data to the four canonical phases: early expansion, late expansion, early contraction, late contraction
   - Use a composite scoring approach: assign each indicator a phase signal (e.g., LEI 6-month rate of change positive = expansion signal; inverted yield curve sustained >3 months = contraction signal)
   - Weigh leading indicators more heavily than coincident or lagging ones for forward-looking assessment
   - Note phase duration — how many months/quarters the current phase has persisted relative to historical median length [VERIFY against NBER cycle dating or equivalent national authority]

2. **Assess leading indicator momentum**
   - Track the direction and rate of change, not just the level — a falling LEI still above zero is a deterioration signal, not yet a contraction signal
   - Check for confirmation across multiple indicator categories (yield curve, credit, labor, manufacturing). Require at least 3 of 5 major categories to agree before calling a phase shift
   - Flag divergences: e.g., strong labor market but weakening ISM and tightening credit suggest late-cycle dynamics

3. **Identify inflection risk**
   - Evaluate whether the economy is mid-phase (stable positioning) or near a turning point
   - Key turning-point signals: yield curve inversion followed by re-steepening, jobless claims breaking above 4-week trend, LEI negative for 6+ consecutive months, credit spreads widening beyond 1 standard deviation from 12-month mean
   - Assign a qualitative probability (low / moderate / elevated) to a phase transition within 6–12 months

4. **Map sector and asset class implications**
   - Early expansion: cyclicals (consumer discretionary, industrials, small caps), high-yield credit, emerging markets tend to outperform
   - Late expansion: quality growth, financials (if curve steep), real assets as inflation hedges
   - Early contraction: defensives (utilities, healthcare, staples), long-duration Treasuries, investment-grade credit
   - Late contraction / trough: position for recovery — upgrade cyclical exposure as stabilization signals appear
   - [VERIFY] Sector rotation patterns are historical tendencies, not guarantees; validate against current structural factors (fiscal policy stance, sector-specific disruptions)

5. **Synthesize positioning recommendation**
   - Combine phase classification, inflection risk, and sector mapping into a coherent narrative
   - State the base case and key risks to the call
   - Specify the data releases or events that would change the assessment (e.g., "two consecutive negative payroll prints would shift our classification from late expansion to early contraction")

## Output

- **Phase classification**: Current phase with confidence level (high / moderate / low) and estimated phase age
- **Leading indicator dashboard**: Table or summary showing each key indicator, its current reading, direction of change, and phase signal
- **Inflection risk assessment**: Probability of phase transition within 6–12 months with supporting evidence
- **Sector/asset implications**: Concise mapping of phase to favored/avoided sectors and asset classes
- **Trigger watchlist**: Specific data points or thresholds that would warrant reclassification

## Quality Checks

- Verify that phase classification is supported by at least 3 independent indicator categories, not a single data series
- Confirm leading indicator data is current — stale data (more than one reporting cycle old) must be flagged
- Ensure the output distinguishes between leading, coincident, and lagging indicators rather than treating them equally
- Check that sector implications account for the current cycle's idiosyncratic features (e.g., pandemic-era distortions, fiscal dominance regimes) rather than relying purely on historical averages
- Validate yield curve and rate data against the relevant central bank's published figures [VERIFY]
- Confirm NBER (or equivalent body) dating is cited correctly when referencing historical cycle lengths [VERIFY]
- Mark any proprietary model outputs or third-party composite scores with their source and vintage date

Attribution

lev-oslev-os
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