Warrior_EA/BLUEPRINT.md

Volatility Meta-Label Pipeline — Architectural Review & Execution Blueprint

Reviewed tree: MQL5/Shared Projects/Warrior_EA (fleet terminal 10CE948A…), 51,445 lines. Date: 2026-09-19.

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0. BLOCKER — READ FIRST: the source tree is 17 days stale and the newer work has no source

The working copy at Documents/Workspaces/Warrior_EA is empty. The only Warrior source on this machine is MQL5/Shared Projects/Warrior_EA, and every file in it is frozen at 2026-09-02 15:33.

The deployed binary the tester actually runs — MQL5/Experts/Warrior/Warrior_EA.ex5 — is dated 2026-09-13 09:13. The source that produced it is gone.

Confirmed absent from disk, machine-wide:

Module	Campaign it belongs to
Signals/SignalDipBuy.mqh	the dip-buy edge (the only surviving edge)
System/DipMeta.mqh	the ALGLIB meta-label
Expert/WarriorExpert.mqh	the session-aware Refresh() fix
WarriorJournal.mqh	the journal + its lookback-leak fix

Corroborating evidence that this tree predates the Sep-11 work: System/TradeChecks.mqh contains the TC* helpers but no TCCanOpen() — the single entry gate added on Sep 11. A machine-wide search found no archive, zip, or backup. The .ex5 is compressed, so no symbol names can be recovered from it (a control search for Warrior in the binary also returned nothing, so that is inconclusive rather than proof of absence).

Consequence for this plan. Sections 1–3 below are correct against the Sep-2 architecture and every line reference is real. But the dip-buy signal, the meta-label scaffolding, and the session-aware refresh — the three things this pipeline would attach to — are not in the tree I can read. Recover or reconstruct the Sep-13 source before executing Phase 3. Phases 1 and 2 are safe to start now; they touch files that do exist.

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1. Architectural review — where the premise and the code differ

Three corrections, because they change what the work actually is.

1a. There is no min-max layer, and no sigmoid time encoding

Expert/Features/FeatureBuilder.mqh (1,357 lines) is the only feature path. What it actually emits:

Feature group	Transform	Line
bar geometry	(close-open)/atr, (high-open)/atr, (low-open)/atr	997–999
trend position	donchPos20/50 — rank in range, bounded [-1,1]	1053–1054
displacement	(close - close[20])/atr, clamped ±10	1059
mean extension	(close - SMA20)/atr, clamped ±10	1063
leg state	dir*(close - legStart)/atr	1086
volume	vol/volBase, absorption, vol×range — all ratios	1119–1129
time	cyclical sin/cos on hour, day-of-week, month	1134–1147
ATR	atr/close, not raw ATR	1148+

There is no MinMax, no Normalize, and no sigmoid anywhere in the tree (grepped). Time is already cyclically encoded, which is the correct choice — a sigmoid on hour would break the 23:00→00:00 wrap.

1b. The real defect is the opposite of the stated one: these inputs are OVER-differenced

Every column above is an integer-order difference, d = 1, ATR-scaled. That is stationary — and it is memory-less. Measured on a synthetic log-price random walk (research/fracdiff.py, validated below):

    d   taps    obs    adf_t    corr-to-level
  0.0      1   6000   -4.362     1.0000     <- raw level: all memory, fails ADF in general
  0.3   2275   3726   -6.947    -0.0106
  0.5    927   5074  -17.799     0.0020
  1.0      2   5999  -53.934    -0.0004     <- WHAT THE EA FEEDS TODAY: memory ~= 0

So the network is handed a stationary series with the price level scrubbed out of it. The one partial exception is smaExtension (close − SMA20), which is a crude low-order memory term — and notably it is one of the four columns the fleet keep-screen voted 24/24 to retain (comment at FeatureBuilder.mqh:1018). That is weak corroboration that retained level information is what the model was missing.

FDF is therefore the right patch — but framed as recovering memory, not as fixing non-stationarity.

1c. The majority-class trap is structural, not a tuning artifact

Expert/AIBase/Inference.mqh:147-153:

ENUM_SIGNAL CExpertSignalAIBase::Argmax3(double pBuy, double pSell, double pNeutral)
  {
   if(pBuy  > pSell && pBuy  > pNeutral) return Buy;
   if(pSell > pBuy  && pSell > pNeutral) return Sell;
   return Neutral;            // also the fallback on any tie
  }

Neutral is both the modal class and the tiebreak. No loss weighting fixes a tiebreak. A 2-class expansion/chop head removes the bucket entirely.

Note the label is already a magnitude question, not a direction one — LegRideLabel() (Labels.mqh:253) asks "does riding this leg pay ≥ LEG_LABEL_MIN_RIDE_ATR", then signs the answer with the leg's own direction. The proposed target keeps the magnitude question, puts it on a fixed clock, and drops the sign. This is a smaller change than it appears.

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2. Violations of the stationarity / time-horizon rules found in the tree

#	Where	Finding	Severity
V1	FeatureBuilder.mqh 997–1186	Every price column is d=1 ATR-normalised → correlation to level ≈ 0. Memory destroyed.	High
V2	Inference.mqh 147	Argmax3 ties resolve to Neutral — majority class is also the tiebreak.	High
V3	Labels.mqh 253 + LegState.mqh 60	Label horizon is event-driven (leg flip), capped at LEG_LABEL_MAX_RIDE_BARS = 200. On H4 that is ~33 days. Nothing constrains it to 48–72h, and nothing constrains it to inside the week.	High
V4	ExpertCustom.mqh ~878	Friday liquidation fires only if a tick lands inside a ±1 minute window (MathAbs(nowMinOfDay - targetMinOfDay) <= 1). A thin Friday close or a shut CFD session means no tick, no liquidation, position carried over the weekend.	Critical
V5	ExpertCustom.mqh ~888	Schedule is evaluated in TimeCurrent() = broker server time. US and EU DST switch on different dates, so any NY-referenced instant drifts by an hour twice a year.	Medium
V6	tree-wide	No swap logic exists at all. DEAL_SWAP is read in the journal (TradeJournalManager.mqh:214) for P&L only. Nothing anywhere reads SYMBOL_SWAP_*.	Medium
V7	Variables/ConfidenceBridge.mqh 15–29	Confidence is computed, published (PublishAIVote) and journalled, but gates nothing — the confidence-scaled management was removed 2026-08-25. There is a bus with no consumer.	Info — this is the hook

V4 is the one to fix regardless of whether the rest of this plan proceeds.

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3. Execution blueprint

Phase 0 — Recover the source (blocking for Phase 3)

1. Check the FLEET terminal's MetaEditor recent-files and any VCS/Dropbox history for the Sep-13 tree.
2. If unrecoverable, reconstruct SignalDipBuy.mqh from the recorded spec: D1, long-only, DIP_ZSCORE entry, inputs DipEntry/DipZ/DipExitMA/DipTrendMA/DipMaxBars, run alone.
3. Re-establish a source-of-truth location that is not only inside the terminal directory.

Phase 1 — Fractional differentiation (research/fracdiff.py, mql5_patches/FracDiff.mqh)

1. Pick d per symbol on real data, not on one series. Run min_ffd() over each fleet instrument and over each era separately. Take the smallest d that passes ADF in every era, not the pooled minimum — this codebase has already been burned by pattern quality inverting across eras.

2. Respect the tap budget. Measured widths:

   d	tau=1e-5	tau=1e-4	tau=1e-3
   0.1	4076	503	62
   0.3	2275	388	66
   0.5	927	200	44

   The stdlib series wrappers return 0.0 in silence past shift 1023. At tau=1e-5, every d ≤ 0.45 exceeds that ceiling and would multiply real weights by silent zeros. FracDiff.mqh therefore calls CopyClose/CopyTickVolume directly and never touches m_Close.GetData(). Default tau = 1e-4 keeps all d ≥ 0.1 under ~500 taps.

3. Add FDF columns alongside the existing ones first, do not replace. Extend the names[]/widths[] table at FeatureBuilder.mqh:441 with ffd_close, ffd_volume. Let the existing fleet keep-screen vote on them, exactly as it voted the ZigZag geometry columns out. Replace d=1 columns only for those the screen actually drops.

4. Raise HistoryBars warm-up by CFracDiff::WarmupBars() — the first taps bars have no valid output and must not be emitted as zeros.

Phase 2 — The volatility target (research/vol_target.py, mql5_patches/VolEstimators.mqh, VolMetaLabel.mqh)

1. Run both targets in parallel and compare, per the brief:
   • (a) Garman-Klass as a continuous regression target,
   • (b) the binary 48–72h expansion label. Score both with walk-forward refits. Require the refit series, never a first fit — a first-fit AUC of 0.68–0.77 on ~4 months has already been proven meaningless here.
2. Use Yang-Zhang, not GK, for anything that gates a multi-day hold. GK assumes the bar opened where the last one closed; index CFDs gap across the daily maintenance break and the weekend, so GK understates the variance the position is actually exposed to. GK stays as the efficient intra-bar estimator and as a feature. Both are implemented.
3. Wire PathBars() into the existing overlap machinery (CLabelOverlap, EffectiveSampleSize(), PurgeBars() in Labels.mqh). A 72h label on H4 spans 18 bars; a raw N overstates significance by ≈ √18 ≈ 4.2×.
4. Budget for the clip. Measured on synthetic H4 with a Friday 16:00 NY flat: 43% of triggers are dropped for not fitting a 48h horizon inside the week (78 of 85 drops). These are dropped as VOL_UNRESOLVED, never labelled chop — labelling them 0 would manufacture a class that correlates with day-of-week, which the network already reads through its sin/cos features. It would learn the calendar.
5. Change the head from 3-class softmax to 2-class; Argmax3 and its Neutral tiebreak go away.

Phase 3 — The meta-label gate (mql5_patches/VolMetaLabel.mqh, SwapWindow.mqh)

1. Do not add the gate as a voting signal module. CExpertSignal has no per-side veto, and returning EMPTY_VALUE silences the entire ensemble rather than one side. A meta-label is a veto, so it belongs on the entry path as one gate — the same shape as TCCanOpen(). Hook: CExpertCustom::Processing() immediately before the CheckOpenLong()/CheckOpenShort() call (ExpertCustom.mqh:528).
2. CVolMetaGate::Allowed() blocks when P(expansion) < 0.70. An unavailable reading also blocks — a filter that degrades to "allow" stops filtering while the log still says it is on.
3. Fix V4 with CWeeklyFlatLatch: fire on the first tick at-or-after the deadline and stay armed until actually flat, instead of a ±1-minute tick lottery. Call it from OnTick and OnTimer so a dead tick stream delays the close rather than cancelling it.
4. Fix V5 with SWNewYorkTime(): derives NY wall-clock from TimeGMT() + US DST rules. Verified against an independent reference implementation across 78,888 hourly instants, 2018–2026: 0 mismatches.
5. Do not hardcode Wednesday for the triple swap. It is per-symbol and the broker publishes it as SYMBOL_SWAP_ROLLOVER3DAYS; several index and metal CFDs bill on Friday. SWTripleSwapDay() reads it.
6. SWTripleSwapCost() prices the carry per SYMBOL_SWAP_MODE and returns false on any mode it cannot price exactly — which blocks the override rather than treating drag as zero.

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4. What was validated, and how

Claim	Method	Result
FFD weights / recurrence	d=1 must reduce to [1,-1]	✓ exactly
ADF estimator	600-rep Monte Carlo of the null	5th pct −2.848 vs textbook −2.86; rejection 4.67% ≈ 5%
Garman-Klass accuracy	4,000 bars × 500 intraday steps, known σ	recovered −4.2% (discrete-sampling bias, caveat 3)
GK efficiency	variance of estimator vs close-to-close	9.97× (theory ~7.4×)
GK non-negativity	algebra + 200k adversarial degenerate bars	non-negative; floor matches 0.1137·ln(C/O)² to 1e-15
Expansion label horizon	synthetic H4, 3 weeks	all spans within [48,72]h; 43% clipped
NY DST offset	independent brute-force reference, 2018–2026	0 / 78,888 mismatches

Two of my own drafting errors were caught by these checks and corrected in place: an initial test series went negative before a log() (producing NaN-spliced false stationarity), and my first draft claimed single-bar GK could be negative — it cannot, and the real hazard is that a corrupt bar yields a plausible positive variance instead. That corrected caveat is now in both the Python and MQL5 headers.

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5. Files delivered

research/fracdiff.py          FFD weights, fixed-width transform, ADF scan, d-selection
research/vol_target.py        GK / Parkinson / Rogers-Satchell / Yang-Zhang + expansion label
mql5_patches/FracDiff.mqh     CFracDiff — 1024-ceiling-safe, log-price, series-order
mql5_patches/VolEstimators.mqh GK/Parkinson/YZ with explicit EMPTY_VALUE and H<L guards
mql5_patches/VolMetaLabel.mqh CVolExpansionLabel + CVolMetaGate (the veto)
mql5_patches/SwapWindow.mqh   NY time, triple-swap day/cost, CWeeklyFlatLatch

None of these have been compiled — no MQL5 toolchain run was performed, and none of them have been copied into the live tree.