Warrior_EA/docs/MIND.md

# The Mind - the trader behind the signal

`Mind/` turns Warrior_EA from "a signal that fires" into "a signal that fires and a trader who
looks at it, sizes it, writes it down and reviews the notebook". The validated dip-buy book is
untouched: the Mind is off the trade path in `MIND_OBSERVE` (the default) and can only take risk
*off* in the acting modes.

## Loop

| step | what | where |
|---|---|---|
| LOOK | every modality reads the closed signal bar into one `SMarketContext` | `Modality*.mqh` |
| RECALL | the reviewer asks how trades in similar conditions have gone | `JournalReviewer.mqh` |
| SIZE | P(win) -> fraction of base risk, never above 1 (AFML ch. 10) | `BetSizer.mqh` |
| WRITE | on close, the trade + context + outcome (R, MAE, MFE) go to a CSV and back to the reviewer | `TradeBook.mqh` |
| ORCHESTRATE | the only class that wires the four | `WarriorMind.mqh` |

Modalities: **price** (z, ATR-distances, regime, volatility percentile), **volume** (tick volume
with the hour-of-day removed, and effort-vs-result), **Wyckoff** (phase, last event, spring,
the reader's verdict), **breadth** (share of the other indices also dipping), **calendar**.

## Modes (`MindMode`)

- `MIND_OBSERVE` (default) - trades exactly as without it. Verified 2026-09-30: SP500 2023-01..09,
  same two trades and the same final balance (100,239.27) with the Mind off and observing.
- `MIND_SIZE` - a setup the journal rates below the book's average gets `m(p)/m(p0)` of the base
  risk (floor `MindMinScale`). Needs `MindMinTrades` closed trades first.
- `MIND_SIZE_GATE` - as SIZE, and a setup the journal rates a coin flip (`p <= 0.5`) is skipped.

## Reading the result

`Common\Files\Warrior_EA\Mind\book_<SYMBOL>_<TF>.csv` - one row per closed trade, 48 columns.
`python research/read_book.py` pools every book and ranks context fields by rank correlation with R,
with the multiple-testing count printed under the table. At the end of each run the Experts log
prints the reviewer's band table, the per-trade Sharpe, PSR(0) and an approximate DSR.

**How to use it honestly.** A field that looks good on the first backtest is a hypothesis. Run the
next period (or another index) with it fixed before believing it; `review_p` vs realised R in
`read_book.py` is the check that the journal's own forecast has any skill.

## Design rules (why it is shaped like this)

- **One column contract.** `ENUM_CTX` + `CtxName()` in `MarketContext.mqh`; modalities write it, the
  book persists it, the reviewer buckets it. No other file spells a column.
- **Open/closed.** A new way of looking = a new `CModality` subclass registered in
  `CWarriorMind::Init()`. Nothing else changes.
- **Authored rules are priors, not gates.** `CWyckoffReader::Bias()` encodes the Wyckoff books'
  reading, but it only reaches the trade through a journal bucket, so the trades decide whether
  "against the structure" is a worse place to buy a dip. In the first test a dip the reader scored
  -0.75 ("distribution phase E") paid +0.50R - one trade, not a verdict, but the reason for this rule.
- **Causal.** Modalities read closed bars only; a trade enters the reviewer when it closes.
  In the tester the book is truncated at Init so one run never informs the next.

## DRY changes made with it

- `System/RegimeMath.mqh` - the efficiency-ratio / variance-ratio arithmetic that lived inside
  `CWarriorSignal`, now shared with the price modality (signal behaviour unchanged).
- `Mind/VolumeFeed.mqh` - the one definition of relative volume. `SignalNeural` and the management
  net's crossing features now use it. **This changes their feature vectors** (names renamed so an
  old model file cannot load): retrain, and do not compare against nets trained before 2026-09-30.
- `System/FeatureScale.mqh` - `FeatSquash`, shared by both.
- `mql5_patches/` holds older snapshots that no build includes (`FracDiff.mqh` has its own
  `VolumeAt` with the old idea). Left alone; delete or migrate when someone needs them.

## Known limits

- The volume level-detrend (`Detrended`) is UNTESTED as a predictor; the book records `rvol_tod`
  (detrended) and `rvol_tod_raw`, so the first journal is its test.
- The reviewer is additive over four dimensions (volatility, volume, Wyckoff verdict, breadth): it
  cannot see interactions and says so in its header. With ~650 trades in five years there is not
  data for more.
- Skipped setups (vol-gated dips, vetoes) are not booked, so the Mind cannot yet learn from the
  trades it did not take.
- The DSR in the run summary uses the large-sample trial variance 1/(T-1); set `MindTrials` to the
  number of configurations really tried.