Feature: The Financials super-cluster is back (BK 84%, MTB 84%, GS 83%) | Top Score Movers

Hi everyone — welcome to this week’s Cmind Earnings Edge.

This is the first real earnings week of the new quarter—and two things matter.

1) The tape will trade the reaction function, not the print. Big banks can “beat” and still sell off if guidance injects uncertainty around NII slope, deposit betas, credit costs, or expense discipline. They can also “meet” and rally if the guide tightens the range and management signals confidence.

2) Dispersion is back early. A Financials-heavy calendar creates cleaner cross-asset read-throughs (rates, curve, credit), while left-tail microcaps behave like volatility pockets that can gap independent of macro.

This week in one screen:

• Regime: Financials super-cluster = “execution premium” week

• Right-tail basket: BK,TB, GS, WFC, BAC, JPM (78–84%)

• Left-tail action: TPET, FNGR, EDUC, TRX, JBHT, SOTK (thin liquidity amplifies gaps)

Feature of the Week — Big Banks kick off earnings season

This week’s feature isn’t a single name—it’s a tradeable cluster. Cmind is showing unusually consistent right-tail probabilities across the big banks, which is exactly the setup folks prefer: liquid, basketable signals with clear macro read-through. See our analysis below for JPM, BAC, C, and WFC.

What the model is saying: When multiple large financials screen 78–84% at the same time (BK/MTB/GS/WFC/BAC/JPM), you’re seeing signal convergence—late-window inputs are aligning rather than diverging. Practically, that supports cleaner construction of:

• beta-neutral bank baskets,
  

• pairs vs. regional banks, and
  

• factor-neutral spreads (Financials long vs. left-tail shorts).
  

Why it matters: Big banks are macro-sensitive microstructures—they translate the curve, funding costs, and credit conditions into earnings faster than most sectors. Their guidance becomes a regime check for rates and risk.

The bank checklist (what to watch):

1. NII + deposit betas: are they tightening the band, widening it, or pushing it out in time? Stability > optimism.
   

2. Credit / reserves: do they frame losses as normalizing or accelerating (consumer + CRE)?
   

3. Expenses: operating leverage vs reinvestment (headcount, comp, tech).
   

4. Markets/IB tone (GS/MS): pipeline conversion and client activity often matter more than the quarter.
   

5. Capital return: buyback cadence and CET1 comfort can cushion downside if the print is “good but not great.”
   

Heatmap Commentary

This week’s heatmap is dominated by a single regime signal: Financials are carrying the early-season “execution premium.” The board is visibly green across the bank complex—BK / MTB, GS, WFC, BAC, JPM, BLK, C, RF, plus a long tail of regionals in the mid-60s to mid-70s. In plain terms, the model is underwriting cleaner prints where the market is most sensitive to NIM cadence, credit normalization, expense control, and capital return posture—and where guide language can create post-print drift.

Outside Financials, the map becomes dispersion-first. Industrials are mixed: IIIN (72%) and RFIL (69%) lean constructive, but JBHT (42%) is a notable left-tail outlier—exactly the kind of “good quarter, cautious guide” setup that can gap on tone. Tech is moderately supportive (TSM 71%, WIT 61%), while the risk cluster is concentrated in smaller, lower-liquidity names across Comm Services (EDUC 41%, FNGR 40%), Materials (TRX 41%, LOOP 43%, PLG 45%), and Energy (TPET 33%).

Top 6 Beats For This Week 

(Highest probabilities on this week’s board)

1. BK (Bank of New York Mellon) — 84% — Financials

2. MTB (M&T Bank) — 84% — Financials

3. GS (Goldman Sachs) — 83% — Financials

4. WFC (Wells Fargo) — 80% — Financials

5. BAC (Bank of America) — 79% — Financials

6. JPM (JPMorgan Chase) — 78% — Financials 

This is a tight right-tail cluster—exactly what you want for basket construction. When multiple large, liquid franchises stack up in the 78-84% range, it’s often a signal that pre-print inputs are converging (less noise, more agreement).

Top 6 Misses For This Week

1. TPET — 33% — Energy

2. FNGR — 40% — Communication Services

3. EDUC — 41% — Communication Services

4. TRX — 41% — Materials

5. JBHT — 42% — Industrials

6. SOTK — 43% — Information Technology 

Market-cap exposure

Large: Banks are index-relevant—guidance can move factor returns.

Mid: Regionals/specialty = deposit competition + credit normalization tell.

Small: Left-tail microcaps = convexity; size to liquidity.

Sector analysis

Financials: the green super-cluster

The most important feature of this week’s heatmap is how broad the Financials strength is:

• Custody/asset servicing: BK (84%)
  

• Large money-center banks: JPM (78%), BAC (79%), WFC (80%), C (77%)
  

• IB/trading exposure: GS (83%), MS (72%)
  

• Asset management: BLK (78%)
  

• Regional/specialty banks: MTB (84%), PNC (75%), RF (76%), BOKF (75%), STT (75%), FHN (78%), etc.

Industrials: mixed-to-fragile

Industrials are not a broad green cluster this week. IIIN (72%) and RFIL (69%) are constructive, but JBHT (42%) is a clear left-tail outlier that raises the “confirmation required” flag. That’s a classic setup where the market may punish any sign of:

• demand softness,
  

• margin compression, or
  

• pricing power erosion.

Information Technology: one strong anchor and watch the left tail

TSM (71%) is the clear IT anchor on the board, while SOTK (43%) sits in the left-tail zone and CNXC (47%) remains miss-leaning. That “barbell” matters because IT prints often trade on:

• backlog / bookings language,
  

• margin bridge clarity, and
  

• confidence in next-quarter demand.

Materials: split tape

FUL (66%) is constructive, but TRX (41%), LOOP (43%), and PLG (45%) sit in miss-leaning territory. This is typical when the market is uncertain whether pricing and demand are stabilizing or rolling over.

Communication Services: red

FNGR (40%) and EDUC (41%) represent a clean red pocket—often the market’s way of demanding proof on monetization and demand stability.

Energy: the single reddest name

TPET (33%) is the lowest-probability name on the heatmap. Left-tail energy small caps can gap sharply on any sign of weaker realizations, cost pressure, or balance sheet stress—especially when liquidity is thin.

Major Score Movers this week (±15 pts)

This week’s score movers split cleanly into two regimes: a broad Financials re-rating and a small-cap left-tail reset. On the upside, the model aggressively upgraded big banks—signaling late-window confidence convergence into earnings (the “execution premium” cluster). In small caps, PKE is the standout re-optimization, with additional upside re-rates in VMAR, HOVR, and RMCF.

On the downside, risk is concentrated in cyclicals/commodities.

✅ Upward shifts 

• PKE: 18% → 64% (+47 pts) — Industrials (Small)

• VMAR: 42% → 63% (+22) — Consumer Discretionary (Small)

• K: 64% → 84% (+20) — Financials (Large)

• GS: 63% → 83% (+19) — Financials (Large)

• MTB: 64% → 84% (+19) — Financials (Large)

• RMCF: 25% → 44% (+19) — Consumer Staples (Small)

• RF: 57% → 76% (+18) — Financials (Large)

• STT: 57% → 75% (+18) — Financials (Large)

• C: 60% → 77% (+17) — Financials (Large)

• HOVR: 48% → 64% (+17) — Industrials (Small)

• WFC: 64% → 80% (+16) — Financials (Large)

• LOOP: 28% → 43% (+15) — Materials (Small)

• BAC: 64% → 79% (+15) — Financials (Large)

• BLK: 64% → 78% (+15) — Financials (Large)

⚠️ Major Downward shifts 

• PLG: 86% → 45% (-41 pts) — Materials (Small)

• TRX: 64% → 41% (-23) — Materials (Small)

• TPET: 53% → 33% (-20) — Energy (Small)

• CVGW: 72% → 54% (-18) — Consumer Staples (Small)

• BMRA: 66% → 50% (-16) — Health Care (Small)

Next week teaser: earnings season broadens

Next week, the calendar typically widens from the banks into a broader set of Financials, plus early prints across additional cyclicals and select defensives—where “read-through” trades become more powerful. The key question will be whether bank guidance supports a stable rates/credit regime (constructive for cyclicals) or introduces enough uncertainty to push the market back toward visibility-first positioning.

About the Model

Cmind AI’s EPS predictions are powered by a machine learning model built for accuracy, objectivity, transparency, and daily updates with latest market information. We ingest over 150 variables across five data modalities—including real-time 10-Q filings, earnings transcripts, governance metrics, and peer signals—to provide early, company-specific EPS forecasts.

Updated daily, our model covers 4,400+ public companies with proven backtests demonstrating improvements in Sharpe and Sortino ratios across portfolios.

 Cmind content is provided for informational purposes only and does not constitute investment research or advice.

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