Learn💼 PortfolioYou Think You're Diversified? Check With Correlation
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You Think You're Diversified? Check With Correlation

Many holdings ≠ diversification. Correlation reveals which positions are effectively the same bet. Use average ρ and high-correlation warnings to spot false diversification.

You Think You're Diversified? Check With Correlation

4-section structure: Concept / How We Compute / How to Read / Caveats.

1. Concept

"Don't put all your eggs in one basket." But what counts as different baskets?

Not "many stocks" — few stocks with low correlation.

If you hold TSMC, UMC, ASE, and Silergy-KY, you hold 4 different companies but essentially one semiconductor sector bet. They rise and fall together. Your "diversified" portfolio is functionally a levered semi ETF.

The correlation coefficient quantifies how similarly two stocks move:

  • ρ = +1 → perfectly in sync
  • ρ = 0 → unrelated
  • ρ = −1 → perfectly opposite

A truly diversified portfolio has average ρ close to zero (or negative).

2. How We Compute

Input

  • Watchlist / portfolio holdings
  • Daily close → simple daily returns
  • 252 trading-day window (configurable)

Two Correlations Side-by-Side

MetricNatureStrength
Pearson ρLinear; assumes normalityIndustry standard
Spearman ρRank-based; distribution-freeRobust to extremes

When Pearson and Spearman diverge significantly, non-linearity or outliers are present — worth attention.

Key Outputs

  • Symmetric correlation matrix (diagonal = 1)
  • Average ρ (upper triangle mean, excluding diagonal)
  • Diversity score:
    • avg ρ < 0.3 → 🟢 High
    • 0.3 ≤ avg ρ < 0.6 → 🟠 Medium
    • avg ρ ≥ 0.6 → 🔴 Low
  • High-correlation warnings: any pair with ρ ≥ 0.85
  • Max / Min pairs

TW and US Computed Separately

Different trading sessions, currencies, holiday calendars — mixing them introduces timezone bias. Shown in two matrices.

Client Cache

  • Same portfolio composition not recomputed for 15 minutes
  • Adding a stock triggers immediate recomputation

3. How to Read

Watchlist: Diversity Badge

Summary bar shows:

Diversity [High / Med / Low]  [⚠ 3]
  • Middle = avg ρ verdict
  • Right red dot + number = count of high-correlation warning pairs
  • Click to expand: avg ρ, sample size, warning list, max/min pairs

Portfolio: Full Heatmap

Portfolio page now shows a correlation matrix below Rolling Sharpe.

Heatmap Color Coding

  • Deep red → strong positive correlation
  • Deep green → strong negative (rare but valuable)
  • Grey → near zero (ideal diversification)

Reading the Matrix

Look for greens and greys, not reds:

  • All red → highly coupled, no real diversification
  • Mixed → partial diversification
  • Grey/green dominant → genuine diversification

Warning List

Below the heatmap, all pairs with ρ ≥ 0.85 are listed. These represent pairs acting as essentially one position. Consider:

  • Removing one of the pair
  • Treating them as a single position and rebalancing

4. Caveats

⚠️ Pearson's Two Assumptions Are Often Violated

  • Linearity
  • Normality

Stock returns frequently violate both. We provide Spearman alongside as a robustness check. When they diverge noticeably, tail events are likely in the data.

⚠️ Sample Length Matters

  • N < 60 days → highly unstable estimates, UI shows red ⚠ Sample < 60 warning
  • N = 252 days → industry standard, reliable
  • N > 500 days → may include structural shifts; can dilute recent relationships

Default 252; user-adjustable.

⚠️ Correlation Is Not Causation

High correlation doesn't mean "A causes B." Could be:

  • Same sector: both ride the same business cycle
  • Same issuer: TSMC (2330) vs TSM — literally the same company
  • Common factor: both react to USD index

Identify the reason before acting. Same ADR → drop one; common factor → consider hedging instead of dropping.

⚠️ Multiple Testing Problem

20 holdings → C(20,2) = 190 pairs. Even with true independence, ~10 pairs will look "significantly correlated" by chance at α = 0.05.

  • 1–2 warnings may be noise
  • More than 5 — seriously reconsider the portfolio

We currently don't apply multiple-testing correction (Bonferroni etc.); that's a planned enhancement.

⚠️ This Is Not Complete Risk Analysis

Correlation tells you co-movement, but not:

  • Volatility magnitude
  • Tail risk (correlations tend to ~1 during crashes — "correlation collapse")
  • Fundamental quality (two weak stocks with low ρ don't cancel each other's weakness)

Correlation is necessary but not sufficient for diversification.


Further Reading

  • Sharpe Ratio: Measuring Investment Efficiency
  • Beta & Volatility: Visualizing Stock Risk
  • CVaR: What Happens If You Hit the Worst 5% (coming Phase 1C)

Try It

  • Open Watchlist — click the Diversity badge in the summary bar
  • Open Portfolio — scroll down to the correlation heatmap
  • Click 📐 for the full formula and parameters

Done reading? Try it hands-on

Practice with CTSstock tools to deepen your understanding

View correlation matrix