CFirstPassageLadder owns the three caches (per-rung up/down first-touch ages
plus the terminal travel) and every question asked of them. The signal keeps
one member where it kept three arrays and a lifespan scalar.
WHAT THIS ENDS. The log-space rung snap existed THREE times: once as
LadderRungFor, twice written out inline inside LadderWinShare - and
LadderRungFor's own header said "Same rule LadderWinShare snaps with, so a
rung chosen here and a rung chosen there are the same rung". A comment asking
a reader to keep three copies equal by hand is the arrangement CMetaFamilies
was built to end. It is now one static RungFor(), so the two rungs agree by
construction.
The bounds test was spelled out at four sites and the "0 means never, tie
goes to the stop" comparison at three. Now Has() and FirstTouch(), once.
The four-site bounds test was also subtly weak: it computed
`idx * COUNT` and tested only the upper end, so a negative index slipped
through into a negative array read. Row() rejects it.
Spread and horizon are ARGUMENTS, not state. The ladder is pure travel in ATR
multiples; what a spread costs and how long the walk ran are facts the caller
supplies. Every answer is now a function of its inputs alone - which is the
point, because this is the barrier arithmetic that failed its own acceptance
test in b5e22a1 and it has never been runnable without a chart, a net and a
broker attached.
BEHAVIOUR UNCHANGED. Each moved body was checked statement-multiset against
its predecessor with the rename map reversed; the only differences are the
substitutions named above.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Found by grouping, not by looking for it.
The candidate-geometry scan kept ten accumulators as ten separate
members. Era start cleared all ten in a ten-line block. The
shutdown-abort path inside the exit-policy simulation cleared
m_geoTrades and nothing else, so nine partial sums - diffSum,
diffSumSq, incSum, candSum, candSl, candTp, incOpen, candOpen,
startTick - survived the abort with the aborted era's values.
The next era then accumulated onto those sums while counting from
zero, so the paired mean is sum/trades with a numerator carrying an
extra era's worth of difference. The paired sigma is worse: diffSumSq
inherits the same contamination, so the scan reports a tighter or wider
spread than it measured depending on what the abort happened to be
holding.
That is the SAME arithmetic that failed its own acceptance test in
b5e22a1, where the reported gain turned out to be monotone in timeout
share. This is not that bug - it needs a shutdown mid-era to fire - but
it lands on the same number, and any geometry reading taken from a
session that was stopped and restarted is suspect.
SGeometryScan now owns all ten with one Reset(). Both sites call it.
A partial reset is no longer something that can be written: there is
one door, and it clears everything behind it.
The struct initialises itself, so the ten constructor-initialiser
entries in Lifecycle.mqh are gone too - MQL5 cannot list struct fields
there, which is a second reason ten loose members was the wrong shape.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The CANDIDATE GEOMETRY line shipped in 05f1a53 said per-candidate
geometry beats the global pair on every SP500 member at 2-3 sigma. It
does not. It said so because a bar that reached neither barrier scored
0 R, and the incumbent's mean is NEGATIVE (-0.07 to -0.21 R). Against a
losing baseline a free zero is a win, so the widest candidate always
came out ahead - and the reported gain ordered itself by timeout share,
not by skill:
PAI 95.1% timed out -> +0.189 R (head measured -2.42 sigma, HARMFUL)
HYB 73.8% -> +0.182 R (head at chance, +0.68 sigma)
CONV 61.8% -> +0.163 R (head measured -2.47 sigma, HARMFUL)
LSTM 27.1% -> +0.158 R (head +1.67 sigma)
Monotone in the timeout share and inverted against the sigma gate. The
acceptance test written when this was built - "the sigma gate predicts
LSTM helps and CONV hurts; if the R difference does not reproduce that
ordering, something is wrong" - is what caught it.
A trade that reaches neither barrier is not worth zero. It is closed at
the horizon, which is what the scheduled close-all does live and what
SimulateTradeOutcome's timeout path already charges. So mark it there:
TripleBarrierLabel now publishes the signed close-to-close travel at the
last bar it actually visited (m_termTravelCache, same validity flag as
the excursion and ladder caches), and LadderOutcomeR prices a timeout
off it instead of returning false. A bar that cannot be evaluated under
BOTH pairs is now dropped whole - scoring one leg and defaulting the
other is the same bug in a smaller costume.
Second defect, same function: CandidateGeometryFor applied neither of
the floors the global derivation applies, so on USDJPY it chose stop
2.00 / target 1.00 - a 67% break-even, forbidden by the 1:2 policy
floor. c3daded in miniature: a selector optimising its own criterion
with no reference to the decision criterion. Both floors now apply, and
the ratio is re-checked AFTER the per-leg rung snap, which can lose it.
Also: the module weight was an unshrunk pooled win rate. USDJPY ConvLSTM
fired 19 times (2.0 effective), won 36.8%, and took module weight 0.37 -
41% of the ensemble's capable weight and the loudest voice on the chart,
off two effective observations. It also lifted the computed vote ceiling
to 26.3 against a 25 threshold, which is why THRESHOLD UNREACHABLE never
printed on a chart whose peak vote is 14 and whose practical ceiling
without that member is 18.8. The pooled rate is now shrunk toward the
coin-flip rate on the era's own OOS bars over 30 prior-equivalent calls,
and the tiers shrink toward the shrunk value rather than the raw one. A
member with ~300 effective calls moves by ~0.4pp; the 19-fire member
goes 0.37 -> ~0.15.
MEASUREMENT ONLY still - no order reads any of this.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Stage 2a of the candidate-conditional geometry the record has named as next and
never built. MEASUREMENT ONLY - no order uses it yet.
WHY THIS AND NOT META-LABELING. Meta-labeling asks take-it-or-skip-it at fixed
geometry, and its verdict stands: real skill, 0 operating points clearing
break-even, and the 4070c5c retraction only moved that bar 1.4pp. The excursion
head, by contrast, just cleared at 3.5-4.6 sigma on LSTM across four eras and
beat the trailing-quantile incumbent. What is learnable here is MAGNITUDE, so
the lever is the geometry, not the veto. A per-candidate rung means a
per-candidate break-even, which a binary gate cannot express.
HOW IT IS SCORED. At each OOS call the same bar is resolved under the incumbent
pair AND under the pair this bar's excursion head would choose, and the paired
difference is accumulated in R with a 2-sigma test. Both legs come from the SAME
first-passage ladder - four array reads, no re-walk, exact even on the ~28% of
bars where both barriers were touched. Mixing the ladder with the price walk
here would measure the discrepancy between two of our own evaluators rather than
the effect of the geometry, which is precisely what f8ac10c had to unpick one
layer over.
The candidate pair applies the GLOBAL derivation's own rule per bar: stop at
BARRIER_SL_QUANTILE of adverse travel, target at the median of favourable.
Neither creates expectancy; what moves is the break-even, which is why the
report quotes R and never a win rate.
FREE VALIDATION. The sigma gate predicts LSTM helps and CONV hurts. If the R
difference reproduces that ordering across members, the head's usefulness is
confirmed by a second, independent measurement. If it does not, something is
wrong and this must not be wired to orders.
Two things caught while writing it, both silent if missed:
- The ladder stores TRAVEL FROM ENTRY, and the scan's mapping is
risk = ladder + spread but reward = ladder - spread, so the two legs convert
with OPPOSITE signs. The stop leg had the sign backwards.
- A GEOMETRY_BUDGET_MS wall clock, because this adds a feature-window build and
a head forward per OOS call to a walk that already runs unchunked at era end
on a single-threaded EA. That is the shape that got the process force-
terminated on 2026-08-21. It stops scoring, never the replay, and the report
prints how many calls it covered.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The //| box blocks were excluded from 0b06f8e and 5efdb48 and were what
remained: 160 of them ran to 10+ lines, the longest to 88. Compressed to their
leading topic sentences - 5 lines for a function header, 8 for a file header -
keeping the box format and the standard MQL5 name/author lines verbatim.
Verified at the BYTE level this time, across every in-scope file: the list of
non-comment lines is byte-identical to HEAD and braces balance. The first check
compared a locale-decoded 'git show' against a UTF-8 read and flagged 25 files
that had not changed at all - every BOM and every non-ASCII line mismatched.
47,696 -> 40,665 lines in scope; comment share 38% -> 26%.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Same pass as 0b06f8e, applied file by file: comment runs of 4+ lines compressed
to their leading topic sentences, capped at 4 lines, whole sentences only.
Warning sentences (NEVER / MUST / trap / would-have) survive the budget.
Every file was checked the same way before committing: the list of non-comment
lines is byte-identical to HEAD, and braces balance. No code was touched.
Panel/, Enumerations/ and the already-terse System headers needed little or
nothing - PooledGate, TradeChecks, BinomialStats and Random came through with
no blocks over the threshold at all.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
EXCURSION_MIN_DISJOINT was 200, sized as "~16k scored bars over a 64-bar
horizon leaves ~250 independent ones". The head scores the OOS SLICE, not the
history. At a 30% split and a 32-bar horizon the ceiling is 4691/32 = 147, so
200 was unreachable and every era printed "[disjoint sample too small]", which
an operator reads as "wait longer". Unpassable by construction - the identical
failure this file already documents one gate down, one layer up.
The trail gate inherited it: m_excTrailScored is a subset of the disjoint bars,
so it failed the same 200 for the same reason, at 130.
Raising OOSSplit or shortening the horizon would clear it and would be fitting
the experiment to the answer. Instead, ask the question the count was standing
in for - is the skill bigger than its own noise:
- The scorer banks one paired Brier difference per DISJOINT window over the
decision rungs (base-head, and trail-head). Disjoint by construction, so no
EffectiveSampleSize deflation applies - striding by the horizon is what buys
that - and paired on identical bars, so the correlation between the two
predictors cancels instead of needing to be estimated.
- passDj and passTrail now require skill >= EXCURSION_SKILL_USEFUL_PCT AND
>= 2 sigma, with the count reduced to a sanity floor of 30.
- Both sigmas print on the verdict line.
This is not a lowered bar. The 2% skill requirement, the oracle control and the
monotone test are untouched, and the sigma test can fail where the count test
never spoke: if +8.5% is noise across 147 windows, it will now say so.
DecisionRungMask() is the single definition of "rung the decision depends on",
called by both the scorer and the report, so the standard error is computed
over exactly the rungs the skill score is. The report's inline copy of the
bracketing test is gone.
Also prints whether the disjoint count is BELOW ITS CEILING or at it, so
"not enough yet" and "not in this configuration" stop reading the same.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Measured from the journal (2026-08-19): the era deep-dive line (~2KB) plus
the excursion verdict, tier re-rank, calibration move, barrier hold and
selection-regressed note each printed EVERY era for EVERY member - ~940
eras/member/day - long after the systems they watch were confirmed
working. Yesterday's file was 1.3GB (70% of it the news-filter calendar
spam the sweep fix already removed).
VerboseMode returns as an INPUT (demoted 2026-08-01 for the marketplace;
that track is dead since the 2026-08-16 pivot) and gains a second job:
false throttles each settled per-era print to eras 0-3 plus every
TRAIN_LOG_EVERY_ERAS-th (25 ~= one deep-dive per ~15min per member);
true restores the per-era firehose, flippable live.
Never throttled: anything that marks a CHANGE - new bests, restores +
eta decays, plateau stage transitions, deploy approvals, warnings,
errors, the label-cache/adoption one-shots, and the combined-vote gate
line (the active system's primary telemetry, still every era).
Semantic fixes over blanket gating:
- barrier hold now ARMS silently and prints only when the hold outlasts
the 2-min report interval - a brief hold every era is the design, the
long hold is the watchdog case the line exists for;
- the ensemble deploy REFUSAL prints immediately when its reason
changes (that is a finding), on cadence when unchanged;
- the filtered-view census prints when its RESULT moves (drawn count,
or strongest vote by >=2pp) and at least every 10th sweep.
NOT COMPILED - user compiles in MetaEditor.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
passTrail demanded m_excTrailScored >= EXCURSION_MIN_SCORED (500), but since
e2c9593 the trail race only scores DISJOINT bars: m_excTrailScored is bounded
by m_excScoredD (~OOS/horizon ~= 256 on SP500 H1) minus the post-ring-clear
warm-up (~8), so every chart failed "[trailing incumbent not warm enough to
race]" at 247-248 of a possible ~256 forever - observed live 2026-08-11 on
all four charts. The counter's statistical population is the same disjoint
sample passDj gates on, so it now takes the same minimum
(EXCURSION_MIN_DISJOINT, 200), reachable with margin after warm-up.
Compile: 0 errors, 0 warnings.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Three findings from the 2026-08-11 audit:
1. The excursion head's trailing-quantile ring was deliberately never cleared
between eras ("a rolling estimate of the market, not of the era") - but
pass 3 re-walks the SAME OOS window every era, so at each walk's restart
the ring still held the outcome masks of the newest OOS bars from the
previous walk: the chronological FUTURE of the bars about to be scored.
For the first ~window+horizon pushes of every era the "trailing" incumbent
was partly a leading one - conservative for the gate (an informed incumbent
is a harder hurdle) but exactly the self-made-artifact class 06d4785 hunts.
The ring now clears at era-score reset; the warm-up bars simply don't score
the trail race, which the m_excTrailN gating already accounts for.
2. skillTrail compared the head's FULL-block Brier (pro-rated by coverage)
against the incumbent's subset sum - valid only if head skill is uniform
across the OOS walk, while the trail-scored subset systematically excludes
each era's warm-up bars. The audit also found m_excBrierHeadD/BaseD/
m_excOosHitsD declared, zeroed and never accumulated (dead since e2c9593
made every scored bar disjoint). The dead trio is replaced by
m_excBrierHeadT: the head's Brier accumulated only on the bars the warm
incumbent also scored, so the race now compares both predictors on an
identical bar set.
3. The AD/Wyckoff feature blocks read GetData with no EMPTY_VALUE guard; a
cold (still-calculating) indicator returns EMPTY_VALUE everywhere, the
sanitize loop rewrote that to 0.0, and the bar SUCCEEDED - so
BufferTempData cached an all-zero Wyckoff block as a success for the whole
bar frame: the one path the f6150ee only-cache-successes rule cannot see,
because it never fails (the ba13eef class, arriving through values that
never fail; a resumed model's era-0 prebuild starts milliseconds after
OnInit). ADIndicatorCold() probes the NEWEST bar - EMPTY_VALUE there means
async warm-up (transient reject, retried), while deep bars beyond the
buffered depth keep the sanitize loop's neutral-fill so degraded history
still trains. Also fixed m_featureCacheValid's declaration comment, which
still described the pre-f6150ee cached-miss semantics.
Compile: 0 errors, 0 warnings.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Measured on exc-race-v3: LSTM era 300s -> 1087s (net 272->748s, "other"
30->337s). My estimate had been "single-digit percent". The cost is
per-DISPATCH, not per-FLOP, and therefore hits EVERY backend: the head is
19k weights and ~2.4 GFLOP an era - seconds of arithmetic - but ~48k
forward/backward calls x several layer submits each, and its 760-wide
layer exceeds the CPU DLL's inline threshold so each one pays a real
handoff. The classifier's own net time tripled too, from contention with
a second pool on an already-full box.
Three changes, all backend-neutral because they remove submits rather
than tune threads:
SCORE ONLY DISJOINT WINDOWS (~64x). Adjacent bars share all but one bar
of their horizon, so 16k consecutive bars were always ~250 independent
observations - the full-sample tally was never worth more than the
disjoint one, it just quoted an n that was ~64x too large. Dropping it
costs nothing statistically and removes 63 of every 64 forward passes.
The two parallel tallies collapse into one, which is also less code.
The trailing ring still advances on every bar: it needs the outcome
SEQUENCE, and that is array lookups, not a forward pass.
TRAIN ON EVERY 4th PRIMARY BAR (4x). The target is low-dimensional and
strongly autocorrelated - neighbouring bars carry near-identical
excursion information - so per-bar training buys resolution the target
does not have. Strided on ATTEMPTS, not acceptances, so a stretch of
unlabelled bars cannot silently change the spacing.
OWN TIMING COLUMN. The head's passes were landing in the era line's
"other" bucket, which is how a 3.6x regression read as an unexplained
jump in the one column nobody attributes. A cost that cannot be seen in
the timing line cannot be traded off against anything.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Beating a frozen global constant is the weakest admissible bar for
replacing a global constant. The honest incumbent is a rolling rung
frequency: it adapts to the volatility regime - exactly what the head
claims to predict - and needs no model, no 760 inputs and no training.
Implemented as a ring of per-bar outcome bitmasks (32 rungs fit one
ulong), sized horizon + EXCURSION_TRAIL_WINDOW. The newest `horizon`
entries are held back UNRESOLVED: a bar's rung outcomes are only known
one horizon later, so using them would be lookahead and would flatter the
incumbent into an opponent the head could never fairly beat. Pass 3 walks
oldest-to-newest, so "pushed more than horizon bars ago" is exactly
"resolved by now". Each push is O(rungs), not O(window).
The head's decision-rung Brier is pro-rated to the trailing estimate's
coverage before the ratio, since the incumbent only scores bars where its
window is warm.
This line is worth reading on its own, independently of the head: if the
trailing quantile beats the global constant, that is a cheap risk-control
win available with no machine learning at all - and it is the same number
either way, so the run answers both questions in one pass.
The ring is deliberately NOT reset per era - it estimates the market, not
the era, and re-warming 500 bars every era would leave the incumbent
unusable over the first chunk of every scoring pass, handing the head a
free win on exactly those bars.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Second-opinion review killed the +4.2% far-rung result, correctly, and
the mechanism is my own bug. A head trained toward {0.05,0.9} converges
to 0.05+0.85p, so its bias is 0.05-0.15p: negative where p is near 1,
POSITIVE where p < 1/3, growing monotonically as the rung gets farther.
Against a baseline frozen at the IS rate, an upward-biased head scores
positive Brier skill whenever the OOS rate merely sits above the IS rate.
Predicted signature: huge negatives near, ~zero at p=1/3, growing
positives far. Observed: -82% ... -0.6% ... +1.2/+2.7/+4.2. The far rungs
were not the clean end of a distorted measurement, they were the other
face of the same artifact. Everything before 25aca83 is void.
The gate was a bare `skill >= 2%` point estimate over 8 rungs x 4
topologies x N eras, reported per era - a best-of-~300 with no interval
and no multiplicity control, which is the shape of the four traps already
documented here. It now needs FOUR things at once:
DECISION RUNGS only the rungs ExcursionQuantile actually reads at the
live geometry (target 1.62, stop 3.31 ATR), fixed
before looking. Skill at 5 ATR is skill about a
distance no order is placed at - and the TARGET side
currently interpolates 1.5/2.0, which measured -2.2%
and -1.3%.
DISJOINT SAMPLE one bar per horizon. Adjacent bars share 63 of 64
horizon bars, so ~16k scored bars is ~250 independent
ones and every SE over the full set is ~8x understated.
VS ORACLE the best constant achievable ON THE SCORED BLOCK,
closed form from H and n (Brier = H*(1-H/n)). A head
that learned only a LEVEL nearer the OOS rate than the
frozen IS constant scores positive against the old
baseline and <= 0 here. This is the control that
separates per-bar skill from base-rate drift.
MONOTONE CURVE P(reach k) must be non-increasing in k. Nothing
constrained 8 independent sigmoids to obey that, and
ExcursionQuantile returns the FIRST crossing - so a
tangled curve is misread exactly where the head is
least sure. Counted and reported, not silently used.
The pass message now also states what a pass would and would not buy:
expectancy is -costs at zero directional edge whatever the stop distance,
and under prop DD limits LOWER variance also lowers P(reach target before
limit), so "better drawdown" is a choice of failure mode, not a win.
Still owed before any Stage 2: a race against a trailing-quantile
incumbent and a vol-feature logistic. Beating a frozen global constant is
the weakest admissible bar for replacing a global constant.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
ExcursionTargets built its 32 binary targets from the classifier's
LABEL_SMOOTH_HIGH/LOW (0.9/0.05). That caps what the head can ever output
at 0.9, and the near ladder rungs have base rates close to 1.0 - almost
every bar travels 0.5 ATR inside a 64-bar horizon. The Brier comparison
is then decided before the net learns anything:
constant at 0.99 -> 0.99*(0.01)^2 + 0.01*(0.99)^2 = 0.0099
head at 0.90 -> 0.99*(0.10)^2 + 0.01*(0.90)^2 = 0.0180 skill -82%
Which is what the first run reported at rung 0.50: PAI -61.8%,
CONV -146%. A property of the target encoding, not of predictability.
Smoothing earns its place on the 3-class head, where it stops one logit
running away inside a softmax competition. There is no competition here
and this head is scored on calibration, so it has to be free to say 0.99
when the answer is 0.99. Hard 1/0 is safe against the runaway smoothing
guards: this is an MSE-on-sigmoid gradient (calcOutputGradients) whose
(target - output) term vanishes as the output approaches the target, not
the unbounded-logit cross-entropy the classifier uses.
The far rungs, where the artifact is smallest, already showed positive
skill on the two topologies with a sequence stage (LSTM 3.00:+1.2%
4.00:+2.7% 5.00:+4.2%, HYBRID similar), so the verdict was being decided
by the most distorted end of the ladder.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Direction is closed - normalised asymmetry fails on three instruments
with a working positive control, and the classifier's own best-of-999
era-cap test agrees (+0.9pp = 1.48 sigma, family-wise p=1.0000). SIZE is
a different question and RANGE clears at ~4x its null.
Checked the denomination before building on that, since the source memo
warns to: m_excUpCache holds (maxHigh - fill)/ATR, so "RANGE is
predictable" is a claim about travel RELATIVE to current ATR, not a
restatement of "ATR is autocorrelated". It is exactly the part a fixed
multiple (stop 3.31*ATR, target 1.64*ATR) discards.
A second small CNet, 760 -> 24 -> 32 sigmoid outputs = P(price reaches
ladder rung k) upward and downward. Survival parameterisation rather than
regressing the multiple, because it needs nothing new from CNet: sigmoid
outputs and the per-neuron delta the `total != 3` branch already applies
(a quantile head would need a linear activation and a pinball gradient in
Network.mqh, Network.cl and the DirectML path, on a class four topologies
share). Targets are free - m_ladderUpAt already records first-touch age
per rung with 0 meaning never reached.
Separate net, not extra outputs on the classifier: more outputs would
change m_outputNeuronsCount, the .nnw shape and the fingerprint, and push
the count off 3 - the exact condition backProp uses to select the joint
softmax gradient the 3-class head depends on. The classifier is
bit-for-bit unaffected and this is removable without trace.
STAGE 1 PLACES NO ORDERS. It reports a Brier skill score against the
constant per-rung base rate - the baseline a fixed ATR multiple already
assumes - with both predictors fitted IS and evaluated OOS, so neither
gets a look at the test set. Positive skill justifies Stage 2 (drive
SL/TP and sizing off ExcursionQuantile, which is defined and deliberately
uncalled). Zero or negative means ATR already carries everything and
Stage 2 must not be built.
Trains only on primary occurrences: the replay queue oversamples for
CLASS balance, and a direction-balanced sample is a biased SIZE sample.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
