Where the best opportunities lie — Energy and the "old-economy cash machines." The long book's center of gravity is unmistakably Energy and value-cyclicals: five of the 25 longs are Energy names (LPG, RRC, IMPP, PARR, CNX), and the bucket screens at an extraordinary average forward EV/EBITDA of just 4.3x with RAVG 92 and FRM 89 — meaning the cheapest multiples in the market are simultaneously the ones with estimates being revised up fastest. That's not an accident: across the full 2,876-name universe, Energy carries the highest conviction of any cyclical sector — a median OM Score of 63.2 (vs. 34.8 for IT) with 91.6% of energy names posting a positive Score. The model is finding torque through two energy paths — natural-gas earnings inflections (RRC at +122% EBITDA, CNX at a staggering +1,010%) and shipping/refining cash gushers (LPG and IMPP throwing off 0.23x FCF/EV, ESEA at 0.29x). The same value logic pulls in Consumer Discretionary (5 longs: BWMX, AFYA, EXPE, GCT, LAUR) and Materials via CF, where the standout is Financials: it's the single strongest sector in the entire universe (median Score 75.9, 95.5% positive), and DLO carries that flag at the top of the book with a perfect 100th-percentile Holy Trinity and +56% forward revenue. The message for these sectors: the market is structurally under-pricing profitable, cash-returning, fundamentally-accelerating businesses — the model sees the best risk-adjusted return in unglamorous places where price hasn't yet caught up to earnings (the cohort's TRS averages just 46).

Where the worst opportunities lie — Information Technology, specifically AI/crypto infrastructure. The short book is a near-monolith: 24 of 25 shorts are Information Technology, which is no surprise given IT screens dead last among growth sectors in the full universe — a median OM Score of just 34.8 and the lowest share of positive-Score names at 67.5%.* But the model isn't shorting "tech" broadly — it's surgically targeting the most speculative corners: AI-infrastructure semis priced for perfection (ALAB at 99x EBITDA, NVTS at 106x sales on revenue falling 45%, AEHR at 663x EBITDA) and crypto miners wearing AI costumes (HUT, RIOT, CORZ, WULF, CLSK, CIFR, APLD), which collectively burn cash — the short cohort averages −40% ROIC, 24x sales, 239x EBITDA, trading at 141% of OM fair value. Critically, the model's own long book also holds seven IT names (ADSK, ADBE, INTU, NVDA, ZM, NTAP, ITRN) — but those are profitable, cash-generative compounders trading at 6–16x EBITDA, the polar opposite of the shorts. That split is the whole story for the sector: IT is the most bifurcated group in the market — the model is long the cheap, durable, cash-rich franchises and short the expensive, unprofitable, high-beta speculation, with the danger flagged in the data (short-cohort beta 3.06, short interest 11.7%, with CLSK at 33% and APLD at 27%). The takeaway for IT as a whole: this isn't a sector to own or avoid wholesale — it's one where dispersion has blown out so far that the same eleven letters of the alphabet contain both the safest longs and the most fragile shorts, and the recent AI/chip sell-off is the market beginning to price exactly that divergence.

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