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Market Wrap

Market Universe — State of the Tape PAPER TRADING

Breadth, rotation & sentiment across 163 names · June 25, 2026
Redacted — proprietary method withheld. The space is kept so you can see where detail exists.

I track 163 liquid US names continuously, and this is my read of the whole tape as of June 25, 2026 — the backdrop I am selecting into, not a trade list. I care less about where the index closed than about how it got there: who is participating, where money is rotating, and where positioning has stretched far enough to matter. The discipline is the same every week, but the conclusions are not — the framework keeps learning, and so do I.

Macro environment

VIX
18.63
10Y−2Y
n/a
HY OAS
2.76
Unemployment
4.3
SPY 20d
-1.45%

Here is how I read the backdrop: volatility sits mid-band at 18.6 (about 1.17% a day), neither complacent nor panicked, high-yield spreads at 2.76 are still contained, so credit is not yet contradicting the tape, and the S&P's trailing month is -1.4%, the trend I am actually trading against.

Volatility is the first thing I price, because it sets the size of every other bet. I scale gross exposure inversely to realised vol — target the risk, not the notional — so a calmer tape lets the book breathe and a violent one pulls it in automatically:

$$\sigma_{\text{daily}}\approx\dfrac{\mathrm{VIX}}{\sqrt{252}}\qquad w_{\text{gross}}\;\propto\;\dfrac{\sigma_{\text{target}}}{\sigma_{\text{daily}}}$$

Source: fred · as of 2026-06-25

Market breadth & participation

Across 163 names in the tracked universe, breadth measures how much of the tape is participating in the trend rather than a handful of leaders. Participation is the share of the universe trading above its own moving averages:

$$\text{Breadth}_{50} \;=\; \frac{1}{N}\sum_{x}\mathbf{1}\!\left[P_x > \mathrm{SMA}_{50}(x)\right]$$
Above SMA50
58%
Above SMA200
71%
Advancers
91
Decliners
72
Avg RSI(14)
53.6
Overbought
11
Oversold
7
Avg 20d
+1.41%

Breadth is my lie-detector for a rally: it tells me whether the index is being lifted by the many or faked by the few. As I read it, 58% sit above their 50-day line, a selective tape that rewards picking over owning the index, longer-term participation still leads the 50-day, so the primary trend is intact even as the near term wobbles, advancers lead decliners 91:72 (an A/D ratio of 1.26), and 11 names are overbought against 7 oversold, the internal tension I weigh for mean-reversion risk.

I count participation and the advance/decline split directly, so the claim is checkable rather than asserted:

$$\mathrm{A/D}=\dfrac{\#\{r_x>0\}}{\#\{r_x<0\}}$$

My read maps to a posture; the exact breadth thresholds that set position sizing stay proprietary and withheld.

Sector rotation

Capital is leaning into Diversified Consumer Services (+15.1% on the trailing month) and away from Technology (-18.5%). That 33.5-point spread is the rotation I am trading: I want the weekly book overweight where both price and participation agree, not where one is dragging the other.

Average 20-day return and SMA50 participation by sector — the raw rotation map under the read above.

SectorNamesAvg 20d% > SMA50
Diversified Consumer Services1+15.06%100%
Chemicals9+14.04%50%
Health Care7+13.18%67%
Unknown2+11.11%100%
Life Sciences Tools & Services2+10.60%100%
Semiconductors9+10.08%100%
Machinery7+9.94%100%
Industrial Conglomerates2+9.20%100%
Banking8+8.67%100%
Consumer products2+8.30%100%
Aerospace & Defense4+5.60%25%
Electrical Equipment3+4.92%100%
Biotechnology7+3.87%67%
Real Estate11+1.30%60%
Textiles, Apparel & Luxury Goods2+0.90%0%
Logistics & Transportation2+0.59%50%
Road & Rail4-0.05%100%
Utilities10-0.10%60%
Hotels, Restaurants & Leisure7-0.29%43%
Communications1-0.64%n/a
Retail10-1.13%44%
Insurance1-1.40%0%
Financial Services12-3.28%45%
Beverages2-4.54%50%
Energy10-5.34%30%
Pharmaceuticals6-6.01%50%
Metals & Mining2-6.98%0%
Media10-7.46%40%
Telecommunication4-10.58%0%
Automobiles1-15.14%n/a
Technology5-18.47%n/a

Momentum leaders & laggards

The strongest names — DD, HUM, AMAT — are where momentum is already doing my work, and I respect a trend until it breaks rather than fading it on a hunch and the laggards — ZTS, CE, ALB — I read as either falling knives or set-ups, and I refuse to confuse the two without a catalyst.

Top movers

Ticker20dRSI
DD+187.16%52.6
HUM+60.66%81.8
AMAT+33.16%62.7
MU+28.08%66.9
NVMI+20.98%n/a
INTC+20.65%65.3
KNSA+18.15%n/a
CVS+16.98%69.1

Bottom movers

Ticker20dRSI
ZTS-31.81%27.3
CE-29.37%34.6
ALB-27.26%33.6
DOW-27.24%27.6
ORCL-25.06%n/a
CHTR-24.59%31.3
NXST-23.38%24.3
CME-22.31%21.3

Sentiment extremes

I read sentiment as a crowding gauge, not a green light. Where the crowd is most bullish I ask what is left to buy; where it is most bearish I ask what is left to sell. The extremes below are useful precisely because they are uncomfortable — they tell me where positioning, not fundamentals, is setting the price.

$$\bar s=\dfrac{1}{N}\sum_x s_x\qquad\sigma_s=\sqrt{\dfrac{1}{N}\sum_x\left(s_x-\bar s\right)^2}$$

Most positive

TickerSentiment20d
SRE+0.96-1.34%
CI+0.95+1.66%
ITW+0.91+5.89%
YUM+0.87-4.53%
PEG+0.87+3.06%
O+0.86-2.80%
EQR+0.86+0.83%
DUK+0.85-1.29%

Most negative

TickerSentiment20d
LOW-0.46-4.97%
CHTR-0.30-24.59%
CMCSA-0.17-16.46%
AEP-0.13+0.00%
DLTR-0.11+8.07%
STT-0.10+7.35%
CAT-0.10+15.48%
MAR-0.09+0.49%

How I read this note

This is my survey of the whole universe I track, not a trade recommendation. Breadth, the advance/decline split and the RSI extremes are standard, publicly defined measures, and I show them in full so you can check my arithmetic. What I keep back is how I combine these readings into position sizing and risk posture — that blend is the edge, and it recalibrates as the evidence does.

Indicator formula reference
RSI: $$\mathrm{RSI}_{14}=100-\frac{100}{1+RS},\quad RS=\frac{\overline{\text{gain}}_{14}}{\overline{\text{loss}}_{14}}$$
MACD: $$\mathrm{MACD}=\mathrm{EMA}_{12}-\mathrm{EMA}_{26},\quad \text{signal}=\mathrm{EMA}_9(\mathrm{MACD})$$
ATR: $$\mathrm{ATR}_{14}=\tfrac{1}{14}\sum TR,\quad TR=\max\big(H-L,\,|H-C_{-1}|,\,|L-C_{-1}|\big)$$
Bollinger: $$\mathrm{BB}=\mathrm{SMA}_{20}\pm 2\,\sigma_{20}$$
Cross-sectional z: $$z=\frac{x-\mu}{\sigma}$$
A standing note on method. I run this book in paper-trading mode, so every fill you see is simulated rather than a realised, audited track record — I would rather state that plainly than flatter the numbers. Nothing here is investment advice, an offer, or a solicitation; it is my own research, published so it can be read and argued with in the open. The blacked-out passages mark the parts of the process I keep proprietary. And because the framework recalibrates every week, where my read was wrong I expect the priors — not my ego — to be the first to say so.