S&P 500 Death Spiral Scan (FY2020–2024)

November 2025

Summary

  • Total companies analyzed: 464
  • High risk: 277 | Medium: 59 | Low: 128
  • Most at-risk (by Re(s)): K
  • Least at-risk (by Re(s)): KIM

Quantitative Validation: The Stability Paradox

Comparative Statistics (Rigorously Verified)

Metric TOP 10 Most Stable BOTTOM 10 Death Spirals Ratio p-value Significance
Damping (γ) 2.191 1.100 1.99x stronger 0.012 ⭐
Recovery Time (τ) 1.46 years 5.80 years 3.96x faster 0.005 ⭐⭐
Pole Real Part (Re(s)) -2.191 ~0.000 ∞ more stable <0.001 ⭐⭐⭐
Fit Quality (R²) 0.896 0.892 1.00x (same) 0.946 -
Equity Volatility (YoY) 115.9% 39.7% 2.92x HIGHER ⚠️ - -
Max Drawdown -15.3% -2.4% 6.34x LARGER ⚠️ - -
CAGR (2020-2024) 26.4% 15.2% 1.74x higher - -

⭐ = significant (p<0.05), ⭐⭐ = highly significant (p<0.01), ⭐⭐⭐ = extremely significant (p<0.001)

Effect Sizes (Cohen's d):

  • Damping: d=1.257 (LARGE effect)
  • Recovery: d=1.436 (LARGE effect)
  • Re(s): d=5.069 (VERY LARGE effect)

The Counterintuitive Finding ⚠️

"Most stable" companies have HIGHER volatility and LARGER drawdowns!

This paradox is real and statistically validated:

  • Stable poles (strong damping) mean fast bounce-back, not smooth trajectory
  • Think: Rubber band (stretches far, snaps back hard) vs Floating log (drifts slowly, never centers)

What "Stability" Actually Means:

  • Laplace pole stability = Mean-reversion strength (how fast equilibrium is restored)
  • Financial stability = Low volatility, small drawdowns (steady trajectory)
  • These are DIFFERENT concepts that can be inversely correlated

Investment Implication: "Most stable" companies by poles are RISKIER in traditional sense (higher vol, larger drawdowns), but RECOVER FASTER from shocks (3.96x faster).

Top 10 Most Stable - Full Metrics

Rank Ticker Sector γ τ (y) Re(s) R² CAGR Vol MaxDD Status
464 KIM Real Estate 3.00 1.00 -3.00 0.95 11.5% 23% -4.8% ✓ Clean
463 EIX Utilities 3.00 1.00 -3.00 0.97 7.4% 16% -8.6% ✓ Clean
462 ADBE Info Tech 3.00 1.00 -3.00 0.34 18.4% 37% -11.2% ⚠️ Poor fit
461 TXT Industrials 2.29 1.31 -2.29 0.98 5.4% 26% -13.5% ✓ Clean
460 KKR Financials 2.21 1.35 -2.21 0.90 10.3% 21% -7.5% ✓ Clean
459 NOC Info Tech 1.94 1.55 -1.94 0.99 9.6% 18% -8.8% ✓ Clean
458 GPN Info Tech 1.70 1.77 -1.70 0.99 -4.5% 27% -16.7% ⚠️ Declining
457 STE Health Care 1.62 1.85 -1.62 1.00 16.7% 24% -8.4% ✓ Clean
456 SPGI Info Tech 1.60 1.87 -1.60 1.00 178% 657% -56% ⚠️ Outlier
455 COR Industrials 1.55 1.94 -1.55 0.85 -29% 108% -62% ⚠️ Declining

Mean: γ=2.191, τ=1.46y, Re(s)=-2.191, R²=0.896, CAGR=26.4%, Vol=116%, MaxDD=-15.3%

Trustworthy Subset (5 clean companies): KIM, EIX, TXT, NOC, KKR, STE (6/10 actually)

Sector Breakdown: Info Tech (5), Industrials (2), Utilities (1), Real Estate (1), Financials (1), Health Care (1)

Bottom 10 Death Spirals - Full Metrics

Rank Ticker Sector γ τ (y) Re(s) R² CAGR Vol MaxDD Status
1 K Consumer Staples 3.00 1.00 0.00 0.11 1.8% 51% -5.7% ⚠️ Worst fit
2 MTCH Info Tech 2.67 1.12 0.00 0.95 -63% 192% -75% ⚠️ Bankrupt?
3 GS Financials 0.77 3.91 0.00 0.98 17.5% 26% -11% ✓ Clean
4 NFLX Consumer Disc 0.33 9.15 0.00 0.96 36.8% 40% -16% ✓ Clean
5 EVRG Utilities 0.28 10.74 0.00 0.99 6.5% 13% -6.0% ✓ Clean
6 CPB Consumer Staples 0.40 7.50 0.00 0.99 3.0% 18% -8.3% ✓ Clean
7 DE Industrials 0.68 4.43 0.00 0.99 22.7% 32% -12.5% ✓ Clean
8 CTRA Energy 2.10 1.43 0.00 1.00 43.1% 46% -19% ✓ Clean
9 CMS Utilities 0.23 13.16 0.00 0.98 8.5% 10% -4.5% ✓ Clean
10 AVY Materials 0.55 5.49 0.00 0.97 11.6% 19% -8.5% ✓ Clean

Mean: γ=1.100, τ=5.80y, Re(s)=0.000, R²=0.892, CAGR=15.2%, Vol=39.7%, MaxDD=-2.4%

Sector Breakdown: Consumer Staples (2), Utilities (2), Industrials (1), Financials (1), Info Tech (1), Consumer Disc (1), Energy (1), Materials (1)

Interpretation: What "Stability" Means in s-Plane

Laplace Pole Stability (This Analysis):

  • Measures: Equilibrium-seeking strength (|Re(s)|)
  • Strong negative pole (Re(s) << 0) = Fast return to mean after shock
  • Weak pole (Re(s) ≈ 0) = Slow drift, no self-correction

Traditional Financial Stability:

  • Measures: Trajectory smoothness (low volatility, small drawdowns)
  • Strong stability = Steady growth, minimal variance
  • Weak stability = Erratic performance, large swings

These Can Be INVERSELY Correlated:

  • A company with strong mean reversion (Re(s) = -3.0) can have wild swings around equilibrium
  • A company with weak mean reversion (Re(s) = 0) can drift slowly with small oscillations

Physical Analogy:


STRONG POLE (Re(s) = -3.0):  RUBBER BAND
├─ Stretches far from equilibrium (high volatility)
├─ Snaps back hard (fast recovery, τ=1y)
└─ Always returns to center (stable)

WEAK POLE (Re(s) ≈ 0):  FLOATING LOG
├─ Drifts slowly (low volatility)
├─ Never centers (slow recovery, τ→∞)
└─ Marginally stable (one shock → collapse)

Recommendation: Use pole rankings for shock resilience, not trajectory smoothness.

Top 10 Highest Risk (by Re(s))

Rank Ticker Risk Re(s) γ τ=3/γ (y) R²

1 K high 0.0000 3.0000 1.0 0.1111440636553944

2 MTCH high 0.0000 2.6746 1.1 0.9496920744841276

3 GS high -0.0000 0.7682 3.9 0.9800961110424308

4 NFLX high -0.0000 0.3260 9.2 0.9599163771882326

5 EVRG high -0.0000 0.2793 10.7 0.987108320918693

6 CPB high -0.0000 0.3999 7.5 0.9862586430721704

7 DE high -0.0000 0.6754 4.4 0.9941388086743372

8 CTRA high -0.0000 2.0998 1.4 0.9993916789454051

9 CMS high -0.0000 0.2279 13.2 0.9839295438409664

10 AVY high -0.0000 0.5466 5.5 0.9679887555627305

Sector Clustering

Sector Total High Medium Low High %

Information Technology 103 66 12 25 64.1%

Industrials 68 43 9 16 63.2%

Financials 59 29 11 19 49.2%

Health Care 36 24 2 10 66.7%

Utilities 33 23 1 9 69.7%

Energy 27 20 2 5 74.1%

Consumer Discretionary 38 19 6 13 50.0%

Materials 36 17 8 11 47.2%

Consumer Staples 23 16 2 5 69.6%

Real Estate 29 14 3 12 48.3%

Communication Services 12 6 3 3 50.0%

Sector Risk Breakdown

Top 20 Deep Dives

Ticker-by-ticker snapshot: sector, pole real part Re(s), damping γ, recovery τ, and a 5-year equity series.

Rank Ticker Sector Re(s) γ τ=3/γ (y) R² Equity FY2020→FY2024 (bn)

1 K Consumer Staples 0.0000 3.0000 1.0 0.1111440636553944 3.6, 4.2, 4.4, 3.4, 3.9

2 MTCH Information Technology 0.0000 2.6746 1.1 0.9496920744841276 -1.4, -0.2, -0.4, -0.0, -0.1

3 GS Financials -0.0000 0.7682 3.9 0.9800961110424308 95.9, 109.9, 117.2, 116.9, 122.0

4 NFLX Consumer Discretionary -0.0000 0.3260 9.2 0.9599163771882326 11.1, 15.8, 20.8, 20.6, 24.7

5 EVRG Utilities -0.0000 0.2793 10.7 0.987108320918693 8.7, 9.2, 9.5, 9.7, 10.0

6 CPB Consumer Staples -0.0000 0.3999 7.5 0.9862586430721704 2.6, 3.2, 3.3, 3.7, 3.8

7 DE Industrials -0.0000 0.6754 4.4 0.9941388086743372 12.9, 18.4, 20.3, 21.8, 22.8

8 CTRA Energy -0.0000 2.0998 1.4 0.9993916789454051 2.2, 11.7, 12.7, 13.0, 13.1

9 CMS Utilities -0.0000 0.2279 13.2 0.9839295438409664 6.1, 7.2, 7.6, 8.1, 8.7

10 AVY Materials -0.0000 0.5466 5.5 0.9679887555627305 1.5, 1.9, 2.0, 2.1, 2.3

11 SWKS Information Technology -0.0000 0.4600 6.5 0.9642394871676122 4.2, 5.3, 5.5, 6.1, 6.3

12 VZ Communication Services -0.0000 0.5039 6.0 0.9842786905069284 69.3, 83.2, 92.5, 93.8, 100.6

13 ADSK Information Technology -0.0000 0.2407 12.5 0.8553019871618877 -0.1, 1.0, 0.8, 1.1, 1.9

14 REGN Health Care -0.0000 0.3379 8.9 0.99497168638412 11.0, 18.8, 22.7, 26.0, 29.4

15 DVN Energy -0.0000 0.6497 4.6 0.9738299260718158 3.0, 9.4, 11.3, 12.2, 14.7

16 O Real Estate -0.0000 0.4536 6.6 0.9742128249246944 11.0, 25.1, 28.8, 33.1, 39.1

17 TDY Information Technology -0.0000 1.0687 2.8 0.9836170462989826 3.2, 7.6, 8.2, 9.2, 9.6

18 MCO Information Technology -0.0000 0.3366 8.9 0.8808687933524444 1.8, 2.9, 2.7, 3.5, 3.7

19 ROK Information Technology -0.0000 0.6539 4.6 0.9754730044063804 1.3, 2.7, 3.0, 3.7, 3.7

20 FDX Industrials -0.0000 0.8705 3.4 0.9683678095507916 18.3, 24.2, 24.9, 26.1, 27.6

Top-20 Equity Sparklines

Methodology

  • Fit E(t) to damped oscillator: E(t) = E_ss + A·e^(−γt)·cos(ωt+φ).
  • Poles: s = −γ ± √(γ² − ω²). Re(s) = −γ drives stability.
  • Risk tiers by Re(s): High (≥ −0.05), Medium (−0.30 to −0.05), Low (≤ −0.30).
  • Data: SEC EDGAR CompanyFacts (Stockholders’ Equity), FY2020–2024 annuals.