S&P 500 Sector Analysis

Overview

5-Year Sector Performance

Annualized returns, volatility, and Sharpe ratios across all 11 S&P 500 sectors from 2021 to 2026.

Total 5-Year Return by Sector

Positive

Annualized Return vs Volatility

Sharpe Ratio Ranking

Sector	ETF	Ann. Return	Volatility	Sharpe	Max Drawdown	Total Return

Question 1

$100K Optimal Allocation

If you had $100,000 to invest across sectors in 2021, which allocation would have maximized your risk-adjusted return by 2026?

Max Sharpe Optimal Risk-Adjusted

$100K grew to $214,800

Ann. Return18.2%

Volatility19.4%

Sharpe0.94

Min Volatility Capital Preservation

$100K grew to $163,200

Ann. Return11.6%

Volatility14.1%

Sharpe0.82

Equal Weight Benchmark

$100K grew to $174,600

Ann. Return12.8%

Volatility18.3%

Sharpe0.70

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Key Finding: The Max Sharpe portfolio concentrates heavily in Energy (~35%) and Industrials (~25%) — the two highest Sharpe ratio sectors over this period. It outperforms equal-weight by ~$40K while maintaining similar volatility. Equal-weight remains a strong benchmark given its simplicity.

Question 2

Hedges & Diversification

Which sectors act as hedges against each other, and how would you build a diversified portfolio?

Sector Correlation Matrix

Lower = better hedge

Min-Volatility Portfolio Weights

Avg Single Sector Vol19.4%

Min-Vol Portfolio14.1%

Vol Reduction~27%

Best Hedge Pairs (Lowest Correlation)

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Key Finding: Energy has the lowest correlations with most other sectors — it's the strongest natural hedge in the S&P 500. A min-volatility blend of all 11 sectors reduces volatility by ~27% versus holding any single sector, without sacrificing positive returns.

Question 3

The 2022 Rate Hike Shock

The Fed raised rates from 0.25% → 4.50% in 2022 — the fastest hiking cycle in 40 years. Who survived and who recovered?

Jan 20220.25%

→

Mar 20220.50%

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Jun 20221.75%

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Sep 20223.25%

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Dec 20224.50%

Sector Returns: 2022 · 2023 · 2024

2022 2023 2024

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2022 Winners

Energy+64.8%

Energy acted as an inflation hedge — oil prices surged as rates rose.

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2022 Casualties

Comm. Services−40.2%

Consumer Disc.−37.5%

Technology−28.2%

Long-duration growth assets hit hardest by rising discount rates.

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Fastest Recovery

Technology+57% in 2023

Comm. Services+55% in 2023

AI tailwinds drove a massive reversal — the hardest-hit sectors bounced back fastest.

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Key Finding: Rate hikes restructured sector leadership entirely. Energy was the only outright winner in 2022. The rate-sensitive growth sectors (Tech, Comm. Services) cratered but staged historic recoveries in 2023 driven by AI. Defensive sectors (Staples, Utilities, Health Care) acted as shock absorbers but lagged the recovery.

Question 4

Momentum vs Mean-Reversion

Which sectors exhibit persistent trends, and which tend to revert after large moves?

Monthly Return Autocorrelation (Lag-1)

Positive = momentum · Negative = mean-reversion

What This Means

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Momentum Sectors

A strong month tends to be followed by another strong month. Trend-following strategies work well here.

↓

Mean-Reverting Sectors

Large moves tend to reverse. "Buy the dip" strategies are more effective here.

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Random Walk Sectors

Neither strategy has significant statistical edge — returns are approximately unpredictable month-to-month.

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Key Finding: Most sectors exhibit weak autocorrelation — short-term price moves don't reliably predict the next month's direction at the sector level. This is consistent with market efficiency. The most actionable signals come from 12-month rolling momentum (medium-term trend following), not month-to-month patterns.

Question 5

Monthly Win Rate Analysis

What's the probability of a positive month in each sector — and does a higher win rate actually predict better overall returns?

Monthly Win Rate by Sector

Win Rate vs Total 5-Year Return

Color = Win/Loss ratio

Win Rate ↔ Total Return r = 0.42 Moderate correlation

Win/Loss Ratio ↔ Total Return r = 0.71 Strong correlation

Highest Win Rate Consumer Staples 68% But modest total return

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Key Finding: Win rate alone is a poor predictor of total returns (r = 0.42). A sector can win less than half its months and still outperform if its winning months are significantly larger than its losing months. Energy has a moderate win rate but outsized winning months — this is what drives its top-ranked 5-year return.

Question 6

Corporate Treasury Recommendation

Scoring sectors on capital preservation, low drawdown, stable return, and risk-adjusted performance.

1

Consumer Staples

XLP

Ann. Return+9.0%

Volatility13.1%

Max Drawdown−16.3%

Sharpe0.68

Lowest volatility, shallowest drawdown, and consistent positive returns. Ideal for capital preservation with modest upside.

Treasury Suitability Scores

Weighted: Vol 30% · Drawdown 30% · Return 20% · Sharpe 10% · Calmar 10%

⚠ Avoid for Treasury: Real Estate (XLRE) & Communication Services (XLC) — high volatility, deep drawdowns (−34% and −47%), and the lowest risk-adjusted returns of any sector.

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Key Finding: For a corporate treasury, capital preservation trumps return maximization. Consumer Staples (XLP) and Utilities (XLU) rank highest — they offer positive returns with the shallowest drawdowns and lowest volatility. A 50/50 blend of both provides even better diversification than either alone.

Question 7

S&P 500 Concentration Risk

How concentrated is the S&P 500, and what does that mean for someone holding an index fund?

S&P 500 Sector Weights (2025)

Return Contribution by Sector

Weight × Annualized Return

Herfindahl-Hirschman Index 0.1619 Cap-weighted S&P 500 Equivalent to only 6.2 independent sectors

HHI — Equal Weight 0.0909 True 11-sector diversification Equivalent to 11.0 independent sectors

Technology Contribution ~46% of cap-weighted index return 32% allocation × 19.8% annual return

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Key Finding: With an HHI of 0.162, the S&P 500 behaves like only ~6 independent sectors rather than 11. A passive index investor is implicitly making a massive bet on Technology. When Tech underperforms (as in 2022), the entire index suffers disproportionately. An equal-weight approach would have provided more genuine diversification.

Additional Insights

Deeper Findings from the Data

β

Sector Beta

Energy (β ≈ 1.22) and Consumer Discretionary (β ≈ 1.18) amplify market moves. Consumer Staples (β ≈ 0.71) and Utilities (β ≈ 0.72) dampen them.

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Seasonal Patterns

November–January is historically the strongest period across sectors ("Santa Claus rally"). August–October shows the most sector divergence.

Nov +2.1% Jan +1.8% Apr +1.6% Sep −0.9% Aug −0.4%

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Drawdown Duration

Communication Services spent the longest consecutive time >5% below its peak — over 18 months. Consumer Staples and Utilities recovered fastest from drawdowns.

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Return Dispersion

The gap between the best and worst sector in any given year ranged from +65% to −40% — sector selection matters enormously year to year.

2022 spread −40% +65%

2023 spread −7% +57%

S&P 500 SectorPerformance Analysis