How everything is calculated
Every number on this site is derived from public data using transparent formulas. If you spot an error or want to reproduce a calculation, you have what you need.
Primer: the semiconductor industry in 90 seconds
Semiconductor companies don't all do the same thing. Knowing where a company sits in the value chain matters because each segment has different margins, cyclicality, and exposure to AI vs broader demand.
The value chain
Design software (EDA) — Synopsys (SNPS), Cadence (CDNS). Sells the tools every chip designer uses. Recurring revenue, very high margins, least cyclical part of the chain.
Chip design (fabless) — NVIDIA (NVDA), AMD, Broadcom (AVGO), Qualcomm (QCOM), Marvell (MRVL). Designs chips but outsources manufacturing. High margins, moderate-to-high cyclicality.
Manufacturing (foundry) — Taiwan Semiconductor (TSM), GlobalFoundries (GFS), United Microelectronics (UMC). Makes chips for everyone. Capital-heavy, huge fab investments, exposed to geopolitics.
Memory — Micron (MU), Samsung (005930.KS), SK Hynix (000660.KS), Western Digital (WDC), Kioxia (285A.T). Most cyclical part of the industry. DRAM/HBM tied to AI; NAND tied to PCs and phones.
Equipment (WFE) — ASML, Applied Materials (AMAT), Lam Research (LRCX), KLA (KLAC), Tokyo Electron (8035.T). Sells the machines that make chips. Leads the cycle by 6–12 months — when fabs order more equipment, more chips are coming.
Integrated device manufacturers (IDMs) — Texas Instruments (TXN), Analog Devices (ADI), NXP (NXPI), Infineon (IFX.DE). Design and manufacture their own chips. Most exposed to industrial, automotive, and broad-based demand — the opposite of the AI trade.
Why semis are cyclical
Building a fab takes 2–4 years and tens of billions of dollars. Demand can shift in months. So supply and demand rarely match: when chips are scarce, prices and earnings surge, capacity gets added; by the time that capacity comes online, demand has often cooled. Cycles tend to last 2–4 years peak-to-peak.
The implication: peak earnings often coincide with cycle tops, not bottoms. Stocks trading at the lowest P/E multiples can sometimes be the most expensive in absolute terms, because the "E" is unsustainable. This is the peak earnings trap, and it's why cycle-aware analysis matters.
What's different about today (mid-2026)
The current cycle is unusual. AI infrastructure demand has decoupled top-tier names (NVDA, AVGO, TSM, ASML, the HBM trio) from the broader cycle. Memory pricing, historically the most cyclical input, is now bifurcated — HBM is sold out into 2027 while NAND tracks a more conventional cycle. Inventory normalization has been uneven. Geopolitical risk (US–China export controls, tariffs) is structural, not transient.
That's the case for splitting sentiment into two parallel gauges. The old "single semi index" approach hides what is actually a two-track market.
Sentiment composite
Two parallel gauges score short-term sentiment from 0 to 100 for two ticker groups. Same six components, different baskets, so the gauges can diverge when the AI economy and the broad-based semi cycle move differently.
Ticker groups
| AI-led | TSM, UMC, GFS, NVDA, AMD, AVGO, MRVL, ALAB, LITE, COHR, MU, 005930.KS, 000660.KS, ASML, AMAT, LRCX, KLAC, TER, 8035.T, ACLS, ONTO, SNPS, CDNS |
| Broad-based | QCOM, 2454.TW, WDC, 285A.T, TXN, ADI, NXPI, STM, ON, MCHP, IFX.DE, WOLF, MPWR, POWI |
Composite formula
| Component | Weight | Rescaling |
|---|---|---|
| Sector breadth (% above 50-day MA) | 25% | linear |
| 14-day RSI | 20% | linear |
| Distance from 50-day MA | 15% | percentile rank, 252-day window |
| Distance from 200-day MA | 15% | percentile rank, 252-day window |
| 20-day relative strength vs SPY | 15% | percentile rank, 252-day window |
| 30-day realized volatility (inverted) | 10% | percentile rank, 252-day window |
+ 0.15 · pctRank(dist_50dma) + 0.15 · pctRank(dist_200dma)
+ 0.15 · pctRank(rs_vs_spy) + 0.10 · pctRank(vol, inverted)
Why percentile rank
Percentile rank against each gauge's trailing 252-day distribution is self-calibrating. Today's reading reflects "where this is vs. where it has been recently," not against an arbitrary historical assumption. So the gauge stays useful in both quiet markets and supercycle conditions.
Score interpretation
| 0–25 | Extreme fear |
| 25–45 | Fear |
| 45–55 | Neutral |
| 55–75 | Greed |
| 75–100 | Extreme greed |
Cycle position
Estimates where the industry sits in its multi-year revenue and capex cycle. Independent from short-term sentiment.
Signals (v1)
| Signal | Weight | Type | Source |
|---|---|---|---|
| SOX year-over-year return | 50% | coincident / lagging | PHLX Semiconductor Index |
| SIA monthly billings YoY | 50% | coincident | SIA press releases |
| Aggregate inventory days (planned) | 0% | forward-looking | EDGAR 10-Q |
| WFE capex YoY (planned) | 0% | forward-looking | EDGAR 10-Q |
Both v1 signals are coincident or lagging. They confirm where we are; they don't predict turns. The forward-looking signals (inventory days, WFE capex YoY) require parsing 10-Q filings and are in development. Until they ship, the cycle composite is best read as "current state of price and revenue trends," not "where the cycle is headed next."
Zone interpretation
| 0–25 | Recovery — emerging from cycle trough |
| 25–55 | Expansion — mid-cycle growth |
| 55–80 | Late expansion — mature growth |
| 80–100 | Peak conditions — readings at historical highs |
Movers and leaders
The overview page shows four short lists derived from the 38-ticker universe:
- Top gainers / laggards — biggest one-day percent moves. Pure return ranking, useful for spotting where today's news is.
- Most extended — trading furthest above their 50-day moving average. These are momentum leaders. Mean-reversion risk is elevated, but extended names can stay extended for weeks during supercycles.
- Lagging trend — trading furthest below their 50-day MA. Either oversold rebound candidates or genuinely broken stories. Either way, worth understanding why.
None of these rankings are buy or sell signals. They highlight where the action is.
Data sources and refresh cadence
| Dataset | Source | Refresh |
|---|---|---|
| Equity prices | Yahoo Finance chart API | daily, after US close |
| Sector sentiment | computed from equities | daily |
| Cycle composite | computed from equities + SIA | daily |
| Movers / leaders | computed from equities | daily |
| Earnings calendar | Yahoo Finance quoteSummary | daily |
| SIA billings | semiconductors.org press releases | monthly, days 1–7 |
| Policy timeline | manually curated, BIS & Federal Register | as events occur |
Known limitations
- Our SOX year-over-year reading is computed as today's 21-day median price vs. the 21-day median centered on the same date one calendar year ago. Other publishers may report different "1-year" figures using rolling, annualized, or total-return methodologies. Our number is honest about what it measures: literal price ratio, smoothed against single-day outliers. It is not directly comparable to "1Y annualized return" figures elsewhere.
- Cycle composite uses 2 of 4 planned signals. Inventory days and WFE capex YoY require parsing 10-Q filings, which is in development. Until they ship, the composite is a coincident/lagging signal, not a forward-looking one.
- The AI gauge contains 4 of the 5 largest semi names by market cap. When NVDA, AVGO, TSM, or ASML have large moves, the composite reflects that concentration. This is a feature for tracking AI infrastructure exposure, not a bug — but worth knowing.
- Yahoo Finance is an unofficial data source and can break without notice.
- Korean and Japanese tickers report on a different trading calendar than US markets. The composite handles missing days gracefully but means weekend US data won't include Friday Asia moves.
- Policy timeline is manually maintained, with a target of adding new BIS rules within 1–2 days of release.
This is not investment advice
Everything on this site is publicly available information processed through transparent formulas. None of it constitutes investment advice. The semiconductor sector is highly cyclical and individual stocks can move significantly on company-specific news. Always do your own research and consult a qualified financial advisor before making investment decisions.