The gate's NormalUpperTail was a hand-rolled Abramowitz & Stegun 26.2.17
approximation. Its own comment gave the reason - "drags a chain of headers
behind it" - and that turned out to be one file: Math\Stat\Normal.mqh
includes only Math.mqh, which includes nothing. Swapped for Cody's rational
approximation in the library (~18 significant digits vs |error| < 7.5e-8).
No past verdict changes: at the z the gate operates on, the difference is
orders of magnitude below DEPLOY_FAMILY_WISE_ALPHA.
Adopting it needed the four bare macros in AI\Network.mqh gone first.
"#define b1 AdamBeta1" collides with an identifier in Math.mqh, so the
include would have macro-expanded the library's own local and failed to
compile - the same landmine that made the original author rename the
approximation's coefficients to ntB1..ntB5 rather than use the reference's
b1..b5. lr, b2 and momentum are the same class of hazard: single-token
global macros in a 52k-line codebase. All four now resolve to the input
names they always aliased, which is a pure textual identity - verified zero
bare occurrences remain.
Also:
- SelectionSort over the buffered signals was O(n^2) with an O(n^2) count of
StructToTime calls, because the comparison rebuilt both datetimes from the
six int date fields every time. Now materialises the keys once and does an
insertion sort; ArraySort cannot permute a struct array. IsEarlier goes
with it, MakeDateTime becomes SignalTime.
- Seven FileOpen sites lacked FILE_SHARE_READ|FILE_SHARE_WRITE, including
AtomicWriteBegin, which stages every model save. All 43 sites now carry
them - an exclusive open fails outright when another process holds the
path, which here has meant a silently skipped save.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
User design (2026-08-19): 'remove the enum menu that selects neural networks... individual
inputs for every NN just like classic signals... the META NN should be integrated into the
voting decision pipeline when enabled... as a bonus meta labelling is applied to enabled NNs.'
- AI_CHOICE is GONE (tombstoned per the stale-.set doctrine). Use_MLP/Use_CONV/Use_LSTM/
Use_CONVLSTM are ordinary bools like the classic votes; the ensemble arithmetic adapts to
any subset because the consensus divisor is the enabled capable weight. Two or more
enabled = ensemble (|ENS1 token + joint gate, exactly the old AI_HYBRID fingerprints, so
existing weight files keep loading); one = the old solo preset; none = classic-only.
- Use_MetaLabeling un-couples META from the direction NNs (the old selector made them
mutually exclusive). S3 ships: CSignalMETA::LiveMetaGate scores each vote-cleared entry
(shared window at bar 1 + proposal descriptor: side, net vote, live geometry, spread/ATR;
pattern one-hot ZEROED - ranking, not calibrated probability, documented in the body) and
vetoes below the cost-adjusted break-even. Entries only; fail-open everywhere, loudly.
- COEXISTENCE HAZARDS closed: VoteCapableWeight()=0 and ProspectiveVote()=false for the
meta target - solo-only until today, a trained META would otherwise sit in the consensus
divisor as a permanent abstainer and shrink every vote by its module weight.
- CERTIFIED == TRADED: the ensemble era verdict replays the identical veto through the same
g_warriorMetaGate pointer over its OOS fired bars (bar re-resolved from the row's own
time; fail-open counted as fires and reported: 'metaGate: N approved, M vetoed, K
unscored'). The overlay deliberately does NOT replay it (veto-filter-in-replay class,
calendar-cliff precedent) - documented at the sweep site. Solo charts' own gate does not
model the veto - the standing solo-gate caveat, documented at the input.
- DB continuity: the pattern/journal DB fingerprint's first slot was (int)AIType;
DbLegacyAiSlot() maps every legacy-expressible config to its OLD value (new 2-3 member
subsets get 100+bitmask, outside the legacy range) so no existing database re-keys.
filterID becomes the enabled roster via one EnabledNNSummary().
- HUD: the meta line shows the gate (armed/(trn), last P vs BE, ok/veto tally); the
armed/disarmed announcement fires on state change via one latch (MetaGateArmedNow), not
only when an entry happens to be proposed.
NOT COMPILED - user compiles in MetaEditor.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The warning lived inside the VerboseMode-gated corpus report, so a
forgotten wipe silently voided an entire 18-year corpus run - the
outdated-row guard rejected the whole replay against leftover rows
and the run appended 35 rows instead of building a corpus. The check
now runs unconditionally at tester OnInit (MetaCorpusStaleCheck): 52
quiet one-row newest-key probes vs the test start, with a loud stop-
wipe-rerun instruction when the DB is newer than the test. Absent
tables probe quietly via FetchNewestTimeKey''s new quiet flag.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
6819bb4 called dbm.FetchRecordCount() from ProcessSignal, but the
method only existed on CDatabaseOperationsManager - CDatabaseManager
never exposed it (nothing outside the DB layer had needed it before).
The 12 compile errors were the usual MQL cascade from one unknown
member.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The historical 1000-row cap existed for a real reason: ProcessSignal
pulled BOTH full tables into MQL struct arrays on every buffered
signal, and UpdateSignalsWeights pulled all 52 per cycle -
materializing thousands of string-bearing structs per event is the
practical limit the cap protected against (SQLite itself has none).
Raising the cap for an 18-year meta-label corpus build would have
made runs crawl; sharding across databases would re-read the same
rows and inherit the same cost.
Every question is now answered inside SQLite, one row or one number
per query, flat in table size:
- FetchOpenTradeEntry: the open (NA) trade''s entryPrice for
pattern+direction, LIMIT 1
- FetchNewestTimeKey: newest row''s yyyymmddhhmm via max ROWID
(rows insert chronologically) - the duplicate/outdated guard
- FetchWinLossCounts: COALESCE''d SUM aggregates with the
before-now bound applied in SQL, replacing the tester-only array
trim (now also active live, where it is harmless by construction)
ProcessSignal semantics preserved exactly: prune -> close opposite
(stop-and-reverse still registers its own row) -> duplicate/outdated
-> one-open-trade -> register. CalculatePatternWinRate''s array walk
becomes WinRateFromCounts; the private FetchTradeRecords wrapper and
ShouldDeleteOldestEntry are gone. DB_MaxRowsPerTable=20000 is now
cheap at any table size.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Every INSERT/UPDATE a backtest journaled printed a phantom "Failed to
execute bound query (error 5126)" + "Failed to insert/update" pair -
11.7k error lines in one tester run - while every row landed
correctly (verified: v5 DB complete and identical in totals to v4,
results populated, zero non-5126 database errors in the whole log).
5126 is ERR_DATABASE_NO_MORE_DATA, SQLite''s DONE: DatabaseRead()
stepped the statement to completion and there is nothing to read back,
which for DML IS the success outcome. The tester agent reports 5126
where the live terminal reports 0 for the same completed step, and
PrepareAndExecuteBound() treated any nonzero code as failure. Success
is now 0 or 5126; genuine failures (busy, locked, constraint, misuse)
surface as other codes and still fail.
No schema or semantics change - the v5 database and its data are
valid as-is; this only stops the misreporting that would bury a real
error.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
1. The expectancy stop was stone dead at shipped defaults. Its only feed -
RecordTradeResult inside CTradeJournalManager::Update() - ran solely under
UseDatabaseRanking, which ships false, so the da54639 halt was armed
(ExpectancyMinTrades=40) and never received a single closed trade. A risk
rule must not be a side effect of an analytics toggle: the journal gains
InitTrackingOnly(), Update() runs unconditionally from OnTick and skips
only the DB insert when no DB was initialized.
2. Below-minimum lots were silently bumped UP to SYMBOL_VOLUME_MIN by
TCNormalizeVolume - correct for a user-entered fixed lot, but in the
risk-sizing path it turned a budget-capped 0.05 into 0.10 on min-0.10/
step-0.01 symbols: double the intended risk, after CapRiskAmount already
clamped, exactly the routine-stop-out-breaches-the-daily-limit scenario
the budget exists to close. CMoneyRiskBase now refuses the trade when the
risk-derived lot is below the broker minimum.
3. All trading was async fire-and-forget (SetAsyncMode(true)) with no
OnTradeTransaction handler and no retry: server retcodes were never
observed. Fail-safe for entries, not for closes - a silently rejected
close rode the position until the next bar (or next day for the timed
close window). Now synchronous, matching the risk-budget flatten's own
already-synchronous CTrade; on an H1 EA the latency is irrelevant.
4. FIXED_LOT bypassed the budget entirely (no CapRiskAmount, no
OpenRiskAtStops) - pre-halt it could commit more than the remaining daily
allowance. A fixed lot cannot be scaled, so the rule is binary: its
loss-to-stop fits the remaining allowance whole or the trade is refused;
unpriceable risk (no SL) is refused while the budget is enabled.
Compile: 0 errors, 0 warnings.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The daily (4%) and total (8%) rules bound how FAST an account can lose. Nothing
noticed WHETHER it was losing. A negative-expectancy signal traded at 1% inside
that envelope breaches no rule and still arrives at zero - it just takes longer,
with every limit green the whole way down. That is the realistic way this EA
destroys an account, and no existing guard could see it.
THE ARITHMETIC THIS ENFORCES. Expected value per trade is p*TP - (1-p)*SL - cost.
With no directional edge p equals SL/(SL+TP), which is also the break-even rate,
so the payoff terms cancel exactly and EV = -cost. Expected P&L is -(trades) x
cost: strictly negative, proportional to activity. Measured here: directional
precision 23-24% against a 25% break-even, flat across every confidence tier,
with 58 points of spread on SP500. Sizing, stop placement and trailing move
variance around that mean; none of them changes its sign.
So every closed position now reports its result in R (net profit over money
actually at risk) and the running mean is tested against zero. Above the
configured minimum sample, if mean + sigma*SE < 0, new entries stop.
- SIGNIFICANTLY below, not merely below. A run of losers is ordinary variance
even for a profitable system; halting on the raw mean would be the same
act-on-noise error the MI gates exist to prevent. Using the standard error
means a wide spread simply demands more trades before the rule can fire.
- NET of swap and commission (ResolveClose already sums all three). Deliberate
and load-bearing: when the edge is zero, cost IS the expectancy, so a gross
version would measure a strategy nobody can trade.
- Reported in R so symbols, lot sizes and balances share one scale and one
mean. Trades without a stop are not scored rather than assigned a guessed R.
- LATCHED across restarts, like the daily halt and for the same reason: a
latch a reattach clears is not a latch. Clearing it means deleting the risk
state file, deliberately, after looking at why.
State is appended to the risk file length-guarded, so files written before this
still load and start their sample at zero rather than misreading.
Defaults 40 trades / 2 sigma; ExpectancyMinTrades = 0 disables it.
This does not make the strategy profitable and is not meant to. It stops paying
tuition on one the results say is losing, and does it on measurement rather than
on a drawdown limit finally being reached.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
- Moves CLayer neuron construction to AI/Impl/Layer.mqh to keep Network.mqh clean
- Unifies four previously duplicated architecture initialisation blocks (MLP/CONV/LSTM/HYBRID) into a single shared function
- Eliminates risk of behavioural drift where one architecture missed a setter, causing mismatched feature sets or targets
Removes standalone AI confidence parameters (MinAIConfidence, MinAIExitConfidence) and replaces them with unified Min_Vote_Open and Min_Vote_Close thresholds that apply to both AI and classic engines. Updates all code comments, report suggestions, and market descriptions accordingly, simplifying configuration and ensuring consistent vote requirements across entry and exit logic.
- Added optional `weighScale` parameter (default -1.0) to `CNeuronBase::Init` and `CLayer::CreateElement`.
- Updated `CNeuronPool::Init` to use LeCun-uniform scaling (1/sqrt(window+1)) for its base initialization.
- Updated `CNet::CNet` to use He-scaled initialization (sqrt(2/neurons)) for dense layers.
- These changes enable more flexible and statistically sound weight initialization, matching the rationale used in OCL-based implementations, leading to better training stability and convergence.
- Define MAX_WEIGHT constant (1.0e6) for weight limits in clusters
- Remove redundant barrier from FeedForward kernel (prevents sync issues)
- Port FeedForwardProof and CalcInputGradientProof kernels for max-pooling (no weights, sliding max)
- Port FeedForwardConv kernel for convolution layers (shared weights, multiple output channels)
- Remove unused code and refactor signal condition logic (CSignalPAI)
