No signals, no secret indicator. SPECTRE publishes the structure the desks trade
around — computed from public market data the same way, every session — and a plain read
of what it means. Levels, not calls.
01 — WHAT WE PUBLISHThe board
Each session, before the open, we publish the day's full structure for NQ, ES, BTC and ETH,
plus a short written read. It's the whole desk's worth of levels — the same families every day, each
computed its own way:
Dealer gammaThe gamma flip (HVL), the call & put walls, and the
GEX strike ladder — where dealer hedging defends, pins, and accelerates.
PivotsFive systems — Classic, Camarilla, Fibonacci, Woodie and
DeMark — at daily, weekly and monthly scope.
Value areasVAH, VAL and POC — where volume actually traded — for the
session and the overnight, plus naked POCs.
VWAPVolume-weighted fair value and its standard-deviation bands.
Prior sessionYesterday's high, low and close — the references every
desk trades off.
Smart moneyOrder blocks and imbalances (FVGs) — the institutional
footprint in the tape.
Expected moveThe session's options-implied range — a one-standard-
deviation envelope.
GoldenConfluence — where three or more independent families stack in
a tight band. Rare, high-conviction, re-derived every session.
02 — WHERE THE NUMBERS COME FROMThe dealer book
Options dealers who sell contracts hedge their risk in the underlying. The size and sign of
that hedging — their gamma exposure (GEX) — changes with price, and it concentrates at
specific strikes. Near heavy positive gamma, dealers buy dips and sell rips, so price tends to
pin; past the flip into negative gamma, they hedge with the move, so price tends to
accelerate. Those concentration points are the levels we publish.
We compute them from publicly available options data — the listed chains for each
instrument — back-solving implied volatility and summing dealer gamma per strike and expiry.
The inputs are public; the read is ours. We don't fabricate, hand-pick, or back-date a single
level.
On the read
The daily desk note is commentary — it describes what the structure suggests and where
reactions are likely. It is deliberately not “buy X, stop Y, target Z.” That's the difference
between research and a signal service, and we stay on the research side on purpose. Reads are
AI-generated and labeled as such.
03 — HOW WE GRADE OURSELVESThe public record
Every level is published in advance and timestamped. After each session, we score the
levels against what the tape actually did and post the result to a public track record anyone can
read. The record is honest by construction: because levels are set before the move and never edited,
a good run can't be faked after the fact and a bad day can't be hidden. We report a reaction
rate, not a profit-and-loss claim — we publish structure, not trades, so we don't market a win
rate or a points total.
03b — THE GRADING RULEWhat “reacted” means
Each level is scored on intraday bars, across roughly 14 months and ~51,000
touches — not a single end-of-day close. A level reacted if, after price first tagged
it, the market moved ≥0.25% in the level's favour (up off a support, down off a resistance)
at some point in the session. The reaction rate is simply reacted touches ÷ total touches, computed
the same way for every family — so the numbers are directly comparable. Most families react about
three times in four.
And we go a level deeper
Reaction rate is honest but blunt — within an instrument the families look similar. So we also grade
every individual line with a symmetric 1:1 (±0.25%) test and rank it best-to-worst per
instrument. That's where the real signal is: the reaction rate is measured per line, so you can
see which hold and which don't. The full per-line ranking — which levels to trust, which to be wary of
— lives in the terminal. Measured live, never back-fit; we show the laggards alongside the winners.
04 — WHO RUNS ITA methodology, not a personality
There's no guru, no track-record screenshot, no “95% win rate.” What stands behind SPECTRE
Markets is this page and the public record — the data source is transparent, the computation is
consistent, and the results are posted whether they're good or bad.