PaPP v2: cartella Analisi (script, risultati, metodologia incroci)

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Merge pull request #11 from pietro1991-dot/devin/1781678159-export-baseline
2026-06-17 07:40:41 +00:00 · 2026-06-17 09:22:50 +02:00 · 2026-06-17 09:12:08 +02:00 · 2026-06-17 06:50:24 +00:00 · 2026-06-17 06:36:24 +00:00
12 changed files with 762 additions and 29 deletions
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+data/*.csv
+scripts/__pycache__/
+*.pyc
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+# PaPP v2 — Analisi dei pattern di incrocio
+
+Questa cartella contiene l'analisi statistica di **cosa succede dopo che due linee
+si incrociano** (le 9 linee del sistema: prezzo, Mediana, 7 MA), gli script per
+riprodurla e i risultati.
+
+Risultati di riferimento: **EURUSD D1, dal 1999** (l'euro reale esiste dal 1999;
+i dati pre-1999 forniti dal broker sono sintetici e vengono esclusi).
+
+---
+
+## 1. Da dove vengono i dati
+
+I dati sono generati in MetaTrader dallo script `PaPP v2/PaPP_CrossExport.mq5`,
+ancorato a **D1** esattamente come l'indicatore. Produce due file:
+
+| file | contenuto |
+|---|---|
+| `PaPP_crosses_<SYM>_D1.csv` | un record per **ogni incrocio** tra le 9 linee |
+| `PaPP_bars_<SYM>_D1.csv` | un record per **ogni giorno D1** (la *baseline*) |
+
+Per ogni record sono salvati:
+- **contesto** al momento dell'evento: distanza dalla Mediana, ampiezza del
+  cluster, trend (sopra/sotto MA365), e le metriche **velocita' / accelerazione /
+  volatilita'** calcolate come **mediana delle 7 scale** (no ATR di MetaTrader);
+- **esiti futuri** a 1/3/5/10/20 giorni: rendimento, max favorevole/avverso,
+  ritorno alla Mediana, e la **traiettoria completa** `cret_1 … cret_20`
+  (rendimento cumulato giorno per giorno, **in percentuale**).
+
+Le 36 coppie sono tutte le combinazioni delle 9 linee; ogni coppia ha 2 direzioni
+(`dir=+1` la 1a linea passa sopra la 2a, `dir=-1` sotto) → 72 casi.
+
+---
+
+## 2. Le 3 correzioni metodologiche (perche' l'analisi e' "onesta")
+
+Una media grezza dei rendimenti dopo un incrocio e' fuorviante. Abbiamo corretto
+i tre problemi tipici:
+
+### 2.1 Bias di periodo → confronto con una baseline nello stesso regime
+Non confrontiamo il rendimento post-incrocio con **zero**, ma con quello di un
+**giorno qualunque nello stesso regime di mercato**. Il regime e' definito da:
+`trend (sopra/sotto MA365) × tercile del cluster × tercile della velocita'`.
+
+`extra-rendimento = rendimento dopo l'incrocio − rendimento medio della baseline
+nello stesso regime`
+
+Se l'extra e' ~0, l'incrocio non aggiunge nulla oltre al contesto.
+(Su EURUSD il drift di fondo della baseline e' risultato ~0, quindi non c'era un
+bias rialzista che gonfiava i numeri.)
+
+### 2.2 "Movimenti piccoli" → effetto in unita' di volatilita'
+L'extra-rendimento e' espresso anche come **frazione della deviazione standard**
+del movimento tipico a quell'orizzonte (`eff = extra / sd_baseline_h`), cosi' un
+0.3% pesa diversamente a 5 o a 20 giorni.
+
+### 2.3 Finestre sovrapposte + tanti test → bootstrap a blocchi + multi-test
+- Gli eventi vicini condividono il futuro (autocorrelazione) → la significativita'
+  e' calcolata con **block bootstrap** (blocchi temporali di 20 giorni), non con il
+  t-test classico.
+- Testiamo 72 casi × 5 orizzonti → alcuni "vincono" per fortuna. Applichiamo la
+  correzione **Benjamini-Hochberg** (`q-value`): consideriamo robusti solo i casi
+  con `q < 0.10`.
+
+---
+
+## 3. Verifiche di correttezza
+
+Lo script `full_table.py` esegue 4 controlli automatici:
+- **V1** la direzione registrata coincide col segno di (A−B) all'incrocio (~99.9%);
+- **V2** `cret_1` coincide esattamente con `ret_1` (differenza 0);
+- **V3** ricalcolo indipendente della media di un pattern (combacia col summary);
+- **V4** la baseline ha drift ~0 (atteso su FX).
+
+---
+
+## 4. Come riprodurre
+
+```bash
+# 1) genera i due CSV da MetaTrader (PaPP_CrossExport.mq5) e copiali in ./data
+# 2) dalla cartella scripts:
+cd scripts
+python excess_analysis.py EURUSD 1999     # summary + top per orizzonte
+python full_table.py      EURUSD 1999     # verifiche + tabella 72 casi
+python plot_trajectories.py EURUSD 1999   # grafico traiettorie extra-rendimento
+```
+Dipendenze: `pandas`, `numpy`, `matplotlib`. I risultati finiscono in `./results`.
+
+---
+
+## 5. Risultati principali (EURUSD, 1999+)
+
+**A) Mean-reversion (il segnale piu' robusto, vale per quasi tutte le coppie):**
+dopo un incrocio il prezzo torna a toccare la Mediana entro 20 giorni nel
+**77–94%** dei casi, in **2–4 giorni** mediani.
+
+**B) Edge direzionali significativi (q<0.10), legati alle scale lunghe:**
+- SALGONO: `MA365xMA7 +`, `MA365xMA182 ±`, `MA365xMA121 −`, `MA121xMA7 +`,
+  `MA121xMA3 +`, `PRICExMA121 −`;
+- SCENDONO: `MA182xMA30 +`, `MA365xMA121 +` (forte a 20g);
+- gli incroci tra MA cortissime e prezzo↔MA brevi sono **neutri** (rumore).
+
+**Lettura onesta:** gli edge direzionali sono **reali ma modesti** (~0.1–0.3 sigma,
+0.2–0.5% di extra, 55–59% di probabilita' di battere la baseline). Il tema
+ricorrente e' la **MA121 (semestrale)**. I casi con pochi campioni (n<40) vanno
+trattati con cautela anche se "significativi".
+
+Vedi `results/tabella_incroci_EURUSD_1999.md` per la tabella completa dei 72 casi.
+
+---
+
+## 6. Contenuto della cartella
+
+```
+Analisi/
+├── README.md                 questo documento
+├── scripts/
+│   ├── _common.py            utility (load, regime, bootstrap, BH)
+│   ├── excess_analysis.py    extra-rendimento + significativita'
+│   ├── full_table.py         verifiche + tabella 72 casi
+│   └── plot_trajectories.py  grafico traiettorie
+├── results/
+│   ├── summary_EURUSD_1999.csv
+│   ├── tabella_incroci_EURUSD_1999.csv
+│   ├── tabella_incroci_EURUSD_1999.md
+│   └── trajectories_EURUSD_1999.png
+└── data/
+    └── README.md             dove mettere i CSV di input (non versionati)
+```
@@ -0,0 +1,13 @@
+# Dati di input
+
+Gli script in `../scripts` leggono da questa cartella i due CSV prodotti dallo
+script MQL5 `PaPP v2/PaPP_CrossExport.mq5` (eseguito in MetaTrader):
+
+- `PaPP_crosses_<SYMBOL>_D1.csv` — un record per **incrocio** tra le 9 linee
+  (prezzo, Mediana, 7 MA), con contesto + esiti futuri.
+- `PaPP_bars_<SYMBOL>_D1.csv` — un record per **ogni giorno D1** (baseline),
+  con lo stesso regime e la traiettoria `cret_1..20`.
+
+I file dati **non sono versionati** (sono grandi e dipendono dal broker).
+Per riprodurre l'analisi: genera i due CSV da MetaTrader e copiali qui, poi
+lancia gli script (vedi `../README.md`).
@@ -0,0 +1,65 @@
+pair,dir,n,raw_1,exc_1,eff_1,pos_1,p_1,raw_3,exc_3,eff_3,pos_3,p_3,raw_5,exc_5,eff_5,pos_5,p_5,raw_10,exc_10,eff_10,pos_10,p_10,raw_20,exc_20,eff_20,pos_20,p_20,q_1,q_3,q_5,q_10,q_20
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+MA182xMA7,1,67,0.0076192537313432805,0.007690816049038089,0.01321026763660675,52.23880597014925,0.927,-0.023750447761194032,-0.03375519602686864,-0.03409498536878306,43.28358208955223,0.618,0.034717462686567155,0.008729420900812945,0.00688042519884507,44.776119402985074,0.926,0.06607283582089549,0.023456423448585822,0.013033680254006787,50.74626865671642,0.865,-0.26800970149253733,-0.31012847852817405,-0.12194423031052547,41.7910447761194,0.143,79.1044776119403,88.05970149253731,5.0,0.9422608695652175,neutro
+MA121xMA7,-1,88,0.07495238636363637,0.06364985841309972,0.10932931685114719,48.86363636363637,0.281,0.07764045454545455,0.043606296058068095,0.044045249356668474,43.18181818181818,0.685,0.10674397727272728,0.06296209107771732,0.049625967512090224,45.45454545454545,0.68,0.11821409090909088,0.025940150893838124,0.014413775963417735,48.86363636363637,0.748,0.1481702272727273,-0.01654939020211934,-0.006507311614475473,45.45454545454545,0.945,73.86363636363636,89.77272727272727,4.0,0.9422608695652175,neutro
+MEDxMA365,-1,37,-0.052988108108108105,-0.044443665841789014,-0.07633945692868081,45.94594594594595,0.662,-0.08400891891891892,-0.06157995647948478,-0.06219983772297179,48.64864864864865,0.624,-0.1621889189189189,-0.14576280294546232,-0.1148884987716481,43.24324324324324,0.176,0.024111081081081055,0.04505525828960639,0.025035182008697174,51.35135135135135,0.761,-0.05749944444444447,0.018377259173368816,0.0072260397876034365,40.54054054054054,0.016,67.56756756756756,88.88888888888889,8.0,0.9422608695652175,neutro
+MA121xMA14,-1,73,0.08883123287671232,0.0738440967816724,0.1268396325759725,53.42465753424658,0.077,0.1377391780821918,0.10205717603308966,0.1030845124068534,49.31506849315068,0.237,0.13806506849315067,0.09286285233037742,0.07319339008513785,54.794520547945204,0.375,0.12088643835616443,0.019819180009174625,0.011012627551783014,45.20547945205479,0.923,-0.061453287671232926,-0.2486090503677838,-0.09775445144285876,41.0958904109589,0.264,65.75342465753424,86.3013698630137,5.0,0.9493714285714286,neutro
+PRICExMA30,-1,427,0.017202927400468377,0.016748936289171738,0.0287691097534581,52.92740046838408,0.482,0.02481250585480094,0.01723528755002068,0.017408782824930823,51.288056206088996,0.739,0.04980238875878221,0.03435935517273575,0.027081633000940863,50.585480093676814,0.609,-0.0037466042154566874,-0.0024782808638988425,-0.0013770692889511526,49.88290398126464,0.965,-0.000713957845433267,-0.007468103997197523,-0.0029364997311411936,47.07259953161593,0.96,81.49882903981265,90.63231850117096,3.0,0.9650000000000001,neutro
+MA182xMA7,-1,66,-0.04358954545454546,-0.05050061533379705,-0.08674328447320295,53.03030303030303,0.129,0.13645151515151513,0.10235803550251647,0.10338840041271781,56.060606060606055,0.28,0.17344772727272728,0.12187603155843105,0.09606123111692019,62.121212121212125,0.074,0.12494348484848483,0.010132061312829493,0.005629931082838358,46.96969696969697,0.957,0.05132227272727275,-0.15314031847959297,-0.06021561887876152,42.42424242424242,0.557,66.66666666666666,89.39393939393939,6.0,0.9650000000000001,neutro
@@ -0,0 +1,79 @@
+# EURUSD (D1, 1999+) — cosa succede dopo ogni incrocio (36 coppie x 2 dir)
+
+extra5/10/20 = extra-rendimento % vs baseline stesso regime; pos10 = % che batte il baseline;
+q10 = significativita' (BH, <0.10 robusto); rev10/20 = % ritorno alla Mediana; btr = giorni mediani.
+
+| coppia | dir | n | extra5 | extra10 | extra20 | pos10 | q10 | rev10 | rev20 | btr | dopo 10g |
+|---|---|---|---|---|---|---|---|---|---|---|---|
+| MA182xMA30 | +1 | 36 | -0.203 | -0.337 | +0.300 | 39% | 0.000 | 64% | 86% | 4 | SCENDE (extra -) |
+| MA365xMA121 | +1 | 15 | +0.209 | -0.130 | -0.902 | 53% | 0.000 | 43% | 71% | 5 | SCENDE (extra -) |
+| MA365xMA7 | +1 | 46 | +0.349 | +0.381 | +0.138 | 52% | 0.000 | 63% | 80% | 4 | SALE (extra +) |
+| MA365xMA182 | -1 | 16 | +0.132 | +0.452 | +0.216 | 69% | 0.000 | 56% | 69% | 4 | SALE (extra +) |
+| MA365xMA121 | -1 | 14 | +0.560 | +0.478 | +1.030 | 79% | 0.000 | 50% | 71% | 3 | SALE (extra +) |
+| MA365xMA182 | +1 | 16 | +0.298 | +0.556 | +0.622 | 56% | 0.000 | 75% | 81% | 4 | SALE (extra +) |
+| MA121xMA7 | +1 | 88 | +0.240 | +0.299 | +0.160 | 57% | 0.010 | 73% | 86% | 3 | SALE (extra +) |
+| MA121xMA3 | +1 | 117 | +0.138 | +0.235 | +0.139 | 59% | 0.027 | 75% | 87% | 4 | SALE (extra +) |
+| PRICExMA121 | -1 | 192 | +0.060 | +0.268 | +0.228 | 56% | 0.048 | 80% | 92% | 3 | SALE (extra +) |
+| MA182xMA121 | +1 | 31 | -0.314 | -0.339 | -0.462 | 35% | 0.151 | 55% | 77% | 2 | neutro |
+| MA121xMA14 | +1 | 73 | +0.132 | +0.138 | +0.249 | 55% | 0.190 | 71% | 84% | 3 | neutro |
+| MA365xMA30 | -1 | 21 | -0.033 | -0.142 | +0.339 | 38% | 0.360 | 67% | 81% | 6 | neutro |
+| MEDxMA30 | +1 | 151 | -0.017 | -0.121 | -0.170 | 48% | 0.461 | 82% | 92% | 3 | neutro |
+| MA30xMA3 | -1 | 259 | -0.046 | -0.110 | -0.136 | 46% | 0.461 | 77% | 90% | 3 | neutro |
+| MEDxMA121 | -1 | 84 | +0.326 | +0.264 | +0.331 | 57% | 0.461 | 75% | 87% | 3 | neutro |
+| MA365xMA3 | -1 | 52 | -0.122 | -0.204 | -0.397 | 44% | 0.472 | 62% | 85% | 5 | neutro |
+| MA182xMA30 | -1 | 35 | -0.386 | -0.375 | -0.125 | 43% | 0.508 | 74% | 89% | 4 | neutro |
+| MEDxMA14 | +1 | 182 | +0.172 | +0.161 | +0.231 | 53% | 0.528 | 68% | 83% | 4 | neutro |
+| MA14xMA7 | -1 | 383 | +0.011 | -0.064 | +0.017 | 47% | 0.572 | 77% | 90% | 3 | neutro |
+| MA365xMA14 | +1 | 28 | +0.111 | -0.216 | +0.220 | 43% | 0.596 | 54% | 81% | 7 | neutro |
+| MA30xMA7 | -1 | 217 | -0.023 | -0.111 | -0.046 | 48% | 0.596 | 78% | 88% | 3 | neutro |
+| PRICExMA30 | +1 | 428 | -0.024 | -0.065 | -0.048 | 47% | 0.596 | 81% | 91% | 2 | neutro |
+| PRICExMA3 | +1 | 1365 | -0.038 | -0.048 | -0.062 | 48% | 0.596 | 69% | 85% | 4 | neutro |
+| PRICExMA7 | +1 | 943 | -0.036 | -0.045 | -0.068 | 48% | 0.596 | 71% | 86% | 3 | neutro |
+| PRICExMA14 | +1 | 623 | +0.002 | +0.018 | -0.002 | 50% | 0.596 | 77% | 90% | 3 | neutro |
+| MA14xMA7 | +1 | 382 | -0.000 | +0.024 | +0.094 | 50% | 0.596 | 74% | 89% | 3 | neutro |
+| MA7xMA3 | -1 | 783 | -0.011 | +0.030 | +0.036 | 50% | 0.596 | 73% | 87% | 3 | neutro |
+| MA121xMA3 | -1 | 117 | +0.022 | +0.135 | -0.053 | 52% | 0.596 | 74% | 91% | 4 | neutro |
+| PRICExMA121 | +1 | 192 | +0.011 | +0.163 | +0.149 | 58% | 0.596 | 79% | 92% | 3 | neutro |
+| PRICExMA365 | +1 | 90 | -0.091 | -0.150 | -0.483 | 50% | 0.637 | 67% | 86% | 3 | neutro |
+| PRICExMED | +1 | 641 | -0.007 | -0.034 | -0.040 | 47% | 0.637 | 87% | 94% | 2 | neutro |
+| MA14xMA3 | -1 | 413 | +0.005 | -0.028 | -0.023 | 48% | 0.637 | 77% | 90% | 4 | neutro |
+| PRICExMA3 | -1 | 1365 | -0.021 | -0.013 | -0.014 | 50% | 0.681 | 70% | 85% | 4 | neutro |
+| MA365xMA3 | +1 | 53 | +0.054 | +0.087 | -0.144 | 47% | 0.758 | 60% | 77% | 4 | neutro |
+| MEDxMA14 | -1 | 185 | -0.044 | -0.082 | -0.053 | 50% | 0.769 | 69% | 83% | 4 | neutro |
+| MEDxMA365 | +1 | 33 | -0.228 | -0.076 | -0.266 | 48% | 0.782 | 76% | 88% | 6 | neutro |
+| MA121xMA30 | -1 | 52 | -0.115 | -0.311 | -0.424 | 48% | 0.794 | 63% | 87% | 5 | neutro |
+| MA182xMA14 | -1 | 46 | +0.171 | -0.209 | -0.075 | 41% | 0.794 | 63% | 87% | 5 | neutro |
+| MA182xMA121 | -1 | 30 | -0.225 | -0.176 | +0.333 | 50% | 0.794 | 70% | 83% | 3 | neutro |
+| MA7xMA3 | +1 | 783 | +0.013 | +0.062 | +0.028 | 52% | 0.816 | 71% | 86% | 4 | neutro |
+| MEDxMA3 | +1 | 274 | +0.040 | +0.073 | +0.006 | 52% | 0.816 | 77% | 88% | 4 | neutro |
+| MEDxMA7 | +1 | 228 | -0.043 | +0.092 | -0.105 | 51% | 0.816 | 74% | 86% | 4 | neutro |
+| MEDxMA182 | +1 | 60 | -0.034 | -0.131 | -0.015 | 45% | 0.926 | 65% | 87% | 4 | neutro |
+| PRICExMA14 | -1 | 622 | +0.006 | +0.048 | +0.026 | 52% | 0.926 | 77% | 90% | 4 | neutro |
+| MA182xMA3 | +1 | 86 | +0.019 | +0.098 | -0.217 | 55% | 0.926 | 79% | 91% | 4 | neutro |
+| PRICExMA182 | +1 | 139 | -0.205 | -0.096 | -0.312 | 50% | 0.928 | 75% | 88% | 3 | neutro |
+| MA365xMA14 | -1 | 27 | +0.015 | -0.059 | +0.134 | 52% | 0.928 | 59% | 89% | 8 | neutro |
+| MA182xMA14 | +1 | 47 | -0.023 | -0.053 | -0.064 | 43% | 0.928 | 74% | 85% | 5 | neutro |
+| MA121xMA30 | +1 | 53 | +0.084 | -0.050 | -0.031 | 42% | 0.928 | 62% | 81% | 3 | neutro |
+| MEDxMA30 | -1 | 142 | +0.038 | -0.048 | +0.050 | 48% | 0.928 | 85% | 94% | 2 | neutro |
+| PRICExMA7 | -1 | 943 | -0.025 | -0.033 | -0.048 | 50% | 0.928 | 72% | 87% | 4 | neutro |
+| MEDxMA3 | -1 | 278 | -0.021 | +0.041 | -0.118 | 47% | 0.928 | 78% | 91% | 3 | neutro |
+| MA365xMA30 | +1 | 22 | -0.224 | +0.056 | +0.540 | 59% | 0.928 | 64% | 90% | 8 | neutro |
+| PRICExMA365 | -1 | 91 | -0.071 | +0.058 | +0.010 | 51% | 0.928 | 68% | 86% | 4 | neutro |
+| PRICExMA182 | -1 | 140 | -0.089 | -0.074 | -0.189 | 46% | 0.942 | 78% | 88% | 4 | neutro |
+| MEDxMA7 | -1 | 240 | +0.061 | -0.026 | -0.095 | 47% | 0.942 | 76% | 88% | 4 | neutro |
+| MA30xMA14 | -1 | 186 | -0.080 | -0.025 | -0.057 | 52% | 0.942 | 73% | 85% | 4 | neutro |
+| MA30xMA14 | +1 | 186 | -0.052 | -0.024 | -0.141 | 52% | 0.942 | 73% | 87% | 3 | neutro |
+| MA30xMA3 | +1 | 258 | -0.037 | -0.013 | +0.042 | 50% | 0.942 | 78% | 90% | 3 | neutro |
+| MEDxMA182 | -1 | 58 | -0.029 | -0.010 | -0.077 | 48% | 0.942 | 78% | 90% | 5 | neutro |
+| MA182xMA3 | -1 | 85 | +0.118 | -0.009 | -0.290 | 51% | 0.942 | 68% | 91% | 5 | neutro |
+| MA30xMA7 | +1 | 217 | +0.012 | +0.011 | +0.060 | 52% | 0.942 | 76% | 88% | 3 | neutro |
+| MA14xMA3 | +1 | 412 | -0.058 | +0.012 | -0.066 | 52% | 0.942 | 75% | 90% | 4 | neutro |
+| MA365xMA7 | -1 | 45 | +0.029 | +0.014 | -0.239 | 51% | 0.942 | 58% | 84% | 6 | neutro |
+| PRICExMED | -1 | 641 | +0.029 | +0.020 | -0.022 | 51% | 0.942 | 87% | 94% | 2 | neutro |
+| MEDxMA121 | +1 | 91 | +0.001 | +0.023 | -0.152 | 52% | 0.942 | 73% | 88% | 4 | neutro |
+| MA182xMA7 | +1 | 67 | +0.009 | +0.023 | -0.310 | 51% | 0.942 | 79% | 88% | 5 | neutro |
+| MA121xMA7 | -1 | 88 | +0.063 | +0.026 | -0.017 | 49% | 0.942 | 74% | 90% | 4 | neutro |
+| MEDxMA365 | -1 | 37 | -0.146 | +0.045 | +0.018 | 51% | 0.942 | 68% | 89% | 8 | neutro |
+| MA121xMA14 | -1 | 73 | +0.093 | +0.020 | -0.249 | 45% | 0.949 | 66% | 86% | 5 | neutro |
+| PRICExMA30 | -1 | 427 | +0.034 | -0.002 | -0.007 | 50% | 0.965 | 81% | 91% | 3 | neutro |
+| MA182xMA7 | -1 | 66 | +0.122 | +0.010 | -0.153 | 47% | 0.965 | 67% | 89% | 6 | neutro |
@@ -0,0 +1,82 @@
+"""Utility condivise per l'analisi PaPP v2.
+
+I dati di input sono i due CSV prodotti dallo script MQL5 `PaPP_CrossExport.mq5`:
+  - PaPP_crosses_<SYM>_D1.csv  (un record per incrocio)
+  - PaPP_bars_<SYM>_D1.csv     (un record per giorno D1 = baseline)
+
+Per default vengono cercati in ../data. Si possono passare percorsi diversi via argv.
+"""
+import os, sys, numpy as np, pandas as pd
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+DATA = os.path.normpath(os.path.join(HERE, "..", "data"))
+HZ = [1, 3, 5, 10, 20]
+
+
+def load(path):
+    df = pd.read_csv(path)
+    df["time"] = pd.to_datetime(df["time"], format="%Y.%m.%d", errors="coerce")
+    if df["time"].isna().all():
+        df["time"] = pd.to_datetime(df["time"], errors="coerce")
+    return df.dropna(subset=["time"]).sort_values("time").reset_index(drop=True)
+
+
+def load_pair(sym="EURUSD", year_min=1999, data_dir=None):
+    d = data_dir or DATA
+    cr = load(os.path.join(d, f"PaPP_crosses_{sym}_D1.csv"))
+    ba = load(os.path.join(d, f"PaPP_bars_{sym}_D1.csv"))
+    if year_min:
+        cr = cr[cr.time.dt.year >= year_min].reset_index(drop=True)
+        ba = ba[ba.time.dt.year >= year_min].reset_index(drop=True)
+    return cr, ba
+
+
+def add_regime(df, edges):
+    """Regime = trend(sopra/sotto MA365) x tercile(cluster) x tercile(velocita')."""
+    tr = (df["trend"] > 0).astype(int)
+    cl = np.digitize(df["cluster_pct"], edges["cl"])
+    ve = np.digitize(df["vel_med"], edges["ve"])
+    out = df.copy()
+    out["regime"] = tr.astype(str) + "_" + cl.astype(str) + "_" + ve.astype(str)
+    return out
+
+
+def regime_edges(ba):
+    return {
+        "cl": np.quantile(ba["cluster_pct"], [1/3, 2/3]),
+        "ve": np.quantile(ba["vel_med"], [1/3, 2/3]),
+    }
+
+
+def block_bootstrap_p(x, nb=2000, bs=20, seed=42):
+    """p-value bilaterale per media != 0 con block bootstrap (gestisce overlap)."""
+    rng = np.random.default_rng(seed)
+    x = np.asarray(x, float)
+    n = len(x)
+    if n < 10:
+        return np.nan
+    nblocks = int(np.ceil(n / bs))
+    idx = np.arange(n)
+    means = np.empty(nb)
+    for k in range(nb):
+        starts = rng.integers(0, n, size=nblocks)
+        pick = np.concatenate([
+            idx[s:s+bs] if s+bs <= n else np.concatenate([idx[s:], idx[:s+bs-n]])
+            for s in starts])[:n]
+        means[k] = x[pick].mean()
+    return 2 * min((means <= 0).mean(), (means >= 0).mean())
+
+
+def benjamini_hochberg(p):
+    """q-value BH per array di p (NaN ammessi)."""
+    p = np.asarray(p, float)
+    out = np.full_like(p, np.nan)
+    idx = np.where(~np.isnan(p))[0]
+    if len(idx) == 0:
+        return out
+    m = len(idx)
+    order = idx[np.argsort(p[idx])]
+    q = p[order] * m / np.arange(1, m + 1)
+    q = np.minimum.accumulate(q[::-1])[::-1]
+    out[order] = np.clip(q, 0, 1)
+    return out
@@ -0,0 +1,69 @@
+"""Fase 2 raffinata: extra-rendimento vs baseline + significativita'.
+
+Per ogni (coppia, direzione) calcola:
+  - rendimento medio grezzo a 1/3/5/10/20 g
+  - EXTRA-rendimento = evento - baseline nello stesso regime (toglie il bias di periodo)
+  - effetto in sigma del movimento tipico a h giorni
+  - quota di eventi che battono la baseline
+  - p-value (block bootstrap) e q-value (Benjamini-Hochberg)
+
+Uso:
+  python excess_analysis.py [SYMBOL] [YEAR_MIN]
+Output:
+  ../results/summary_<SYM>_<YEAR>.csv  + stampa dei top a 5/10/20 g
+"""
+import os, sys, numpy as np, pandas as pd
+from _common import load_pair, add_regime, regime_edges, block_bootstrap_p, benjamini_hochberg, HZ, HERE
+
+SYM = sys.argv[1] if len(sys.argv) > 1 else "EURUSD"
+YEAR = int(sys.argv[2]) if len(sys.argv) > 2 else 1999
+RESULTS = os.path.normpath(os.path.join(HERE, "..", "results"))
+
+cr, ba = load_pair(SYM, YEAR)
+print(f"[{SYM} {YEAR}+] incroci={len(cr)}  baseline={len(ba)}")
+
+edges = regime_edges(ba)
+cr = add_regime(cr, edges)
+ba = add_regime(ba, edges)
+
+base_mean = {h: ba.groupby("regime")[f"cret_{h}"].mean() for h in HZ}
+base_glob = {h: ba[f"cret_{h}"].mean() for h in HZ}
+base_sd   = {h: ba[f"cret_{h}"].std()  for h in HZ}
+
+rows = []
+for (pair, d), g in cr.groupby(["pair", "dir"]):
+    n = len(g)
+    if n < 30:
+        continue
+    rec = {"pair": pair, "dir": int(d), "n": n}
+    for h in HZ:
+        ev = g[f"cret_{h}"].values
+        bexp = g["regime"].map(base_mean[h]).fillna(base_glob[h]).values
+        exc = ev - bexp
+        rec[f"raw_{h}"] = np.nanmean(ev)
+        rec[f"exc_{h}"] = np.nanmean(exc)
+        rec[f"eff_{h}"] = np.nanmean(exc) / base_sd[h]
+        rec[f"pos_{h}"] = (exc > 0).mean()
+        rec[f"p_{h}"]   = block_bootstrap_p(exc)
+    rows.append(rec)
+
+res = pd.DataFrame(rows)
+for h in HZ:
+    res[f"q_{h}"] = benjamini_hochberg(res[f"p_{h}"].values)
+
+os.makedirs(RESULTS, exist_ok=True)
+outp = os.path.join(RESULTS, f"summary_{SYM}_{YEAR}.csv")
+res.to_csv(outp, index=False)
+
+print(f"vol giornaliera prezzo (sd cret_1) = {ba['cret_1'].std():.3f}%")
+print(f"baseline drift 5/10/20g = {base_glob[5]:.3f}% / {base_glob[10]:.3f}% / {base_glob[20]:.3f}%")
+for h in [5, 10, 20]:
+    sig = res[res[f"q_{h}"] < 0.10].copy()
+    sig["ae"] = sig[f"eff_{h}"].abs()
+    sig = sig.sort_values("ae", ascending=False).head(12)
+    print(f"\n=== TOP {h}g (q<0.10) ===")
+    for _, r in sig.iterrows():
+        print(f"  {r['pair']:13s} dir={int(r['dir']):+d} n={int(r['n']):5d} "
+              f"exc={r[f'exc_{h}']:+.3f}% eff={r[f'eff_{h}']:+.2f}sd "
+              f"pos={r[f'pos_{h}']*100:.0f}% q={r[f'q_{h}']:.3f}")
+print(f"\nsalvato: {outp}")
@@ -0,0 +1,83 @@
+"""Verifiche di correttezza + tabella completa 36 coppie x 2 direzioni.
+
+Verifiche:
+  V1 la direzione registrata coincide col segno di (A-B) all'incrocio
+  V2 cret_1 coincide con ret_1
+  V3 ricalcolo indipendente della media di un pattern
+  V4 baseline drift ~0
+
+Tabella: per ogni (coppia, dir) extra-rendimento 5/10/20g, quota che batte il baseline,
+q-value a 10g, tasso di ritorno alla Mediana (rev10/rev20), giorni mediani al ritorno,
+ed etichetta verbale "dopo 10g".
+
+Uso:
+  python full_table.py [SYMBOL] [YEAR_MIN]
+Output:
+  ../results/tabella_incroci_<SYM>_<YEAR>.csv (+ .md)
+"""
+import os, sys, numpy as np, pandas as pd
+from _common import load_pair, add_regime, regime_edges, block_bootstrap_p, benjamini_hochberg, HZ, HERE
+
+SYM = sys.argv[1] if len(sys.argv) > 1 else "EURUSD"
+YEAR = int(sys.argv[2]) if len(sys.argv) > 2 else 1999
+RESULTS = os.path.normpath(os.path.join(HERE, "..", "results"))
+
+cr, ba = load_pair(SYM, YEAR)
+
+# ---------------- VERIFICHE ----------------
+sub = cr[cr.pair == "PRICExMED"]
+chk = ((sub.price - sub.med) > 0).astype(int).replace(0, -1)
+print(f"[V1] PRICExMED dir vs segno(price-med): {(np.sign(sub.dir)==np.sign(chk)).mean()*100:.1f}% (atteso ~100%)")
+print(f"[V2] max|cret_1 - ret_1| = {(cr.cret_1-cr.ret_1).abs().max():.6f} (atteso 0)")
+g0 = cr[(cr.pair=='MA121xMA7') & (cr.dir==1)]
+print(f"[V3] MA121xMA7+ n={len(g0)} media cret_10 = {g0.cret_10.mean():.4f}%")
+print(f"[V4] baseline cret_10 medio={ba.cret_10.mean():.4f}% sd={ba.cret_10.std():.3f}% (drift ~0)")
+
+# ---------------- TABELLA ----------------
+edges = regime_edges(ba)
+cr = add_regime(cr, edges); ba = add_regime(ba, edges)
+bmean = {h: ba.groupby("regime")[f"cret_{h}"].mean() for h in HZ}
+bglob = {h: ba[f"cret_{h}"].mean() for h in HZ}
+bsd   = {h: ba[f"cret_{h}"].std()  for h in HZ}
+
+rows = []
+for (pair, d), g in cr.groupby(["pair", "dir"]):
+    rec = {"pair": pair, "dir": int(d), "n": len(g)}
+    for h in HZ:
+        ev = g[f"cret_{h}"].values
+        bexp = g["regime"].map(bmean[h]).fillna(bglob[h]).values
+        exc = ev - bexp
+        rec[f"raw_{h}"] = np.nanmean(ev)
+        rec[f"exc_{h}"] = np.nanmean(exc)
+        rec[f"eff_{h}"] = np.nanmean(exc) / bsd[h]
+        rec[f"pos_{h}"] = (exc > 0).mean() * 100
+        rec[f"p_{h}"] = block_bootstrap_p(exc)
+    rec["rev10"] = g["rev_10"].mean() * 100
+    rec["rev20"] = g["rev_20"].mean() * 100
+    rec["btr_med"] = g["bars_to_revert"].median()
+    rows.append(rec)
+res = pd.DataFrame(rows)
+res["q10"] = benjamini_hochberg(res["p_10"].values)
+
+def verb(r):
+    if r["q10"] < 0.10 and r["exc_10"] > 0: return "SALE (extra +)"
+    if r["q10"] < 0.10 and r["exc_10"] < 0: return "SCENDE (extra -)"
+    return "neutro"
+res["dopo_10g"] = res.apply(verb, axis=1)
+res = res.sort_values(["q10", "exc_10"]).reset_index(drop=True)
+
+os.makedirs(RESULTS, exist_ok=True)
+csvp = os.path.join(RESULTS, f"tabella_incroci_{SYM}_{YEAR}.csv")
+res.to_csv(csvp, index=False)
+
+md = [f"# {SYM} (D1, {YEAR}+) — cosa succede dopo ogni incrocio (36 coppie x 2 dir)", "",
+      "extra5/10/20 = extra-rendimento % vs baseline stesso regime; pos10 = % che batte il baseline;",
+      "q10 = significativita' (BH, <0.10 robusto); rev10/20 = % ritorno alla Mediana; btr = giorni mediani.", "",
+      "| coppia | dir | n | extra5 | extra10 | extra20 | pos10 | q10 | rev10 | rev20 | btr | dopo 10g |",
+      "|---|---|---|---|---|---|---|---|---|---|---|---|"]
+for _, x in res.iterrows():
+    md.append(f"| {x['pair']} | {int(x['dir']):+d} | {int(x['n'])} | {x['exc_5']:+.3f} | "
+              f"{x['exc_10']:+.3f} | {x['exc_20']:+.3f} | {x['pos_10']:.0f}% | {x['q10']:.3f} | "
+              f"{x['rev10']:.0f}% | {x['rev20']:.0f}% | {x['btr_med']:.0f} | {x['dopo_10g']} |")
+open(os.path.join(RESULTS, f"tabella_incroci_{SYM}_{YEAR}.md"), "w").write("\n".join(md))
+print(f"\nsalvato: {csvp} (+ .md)  righe={len(res)}")
@@ -0,0 +1,43 @@
+"""Grafico delle traiettorie di extra-rendimento (giorno per giorno) dopo l'incrocio.
+
+Disegna l'extra-rendimento cumulato (cret_1..20 - baseline stesso regime) per un
+insieme di pattern (default: i piu' consistenti legati alla MA121/MA365).
+
+Uso:
+  python plot_trajectories.py [SYMBOL] [YEAR_MIN]
+Output:
+  ../results/trajectories_<SYM>_<YEAR>.png
+"""
+import os, sys, numpy as np
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from _common import load_pair, add_regime, regime_edges, HERE
+
+SYM = sys.argv[1] if len(sys.argv) > 1 else "EURUSD"
+YEAR = int(sys.argv[2]) if len(sys.argv) > 2 else 1999
+RESULTS = os.path.normpath(os.path.join(HERE, "..", "results"))
+HZ = list(range(1, 21))
+
+cr, ba = load_pair(SYM, YEAR)
+edges = regime_edges(ba)
+cr = add_regime(cr, edges); ba = add_regime(ba, edges)
+bmean = {h: ba.groupby("regime")[f"cret_{h}"].mean() for h in HZ}
+bglob = {h: ba[f"cret_{h}"].mean() for h in HZ}
+
+sel = [("MA121xMA7", 1), ("MEDxMA121", -1), ("PRICExMA121", -1), ("MA121xMA3", 1), ("MA365xMA7", 1)]
+plt.figure(figsize=(11, 6))
+for pair, d in sel:
+    g = cr[(cr.pair == pair) & (cr.dir == d)]
+    if len(g) < 20:
+        continue
+    exc = [(g[f"cret_{h}"] - g["regime"].map(bmean[h]).fillna(bglob[h])).mean() for h in HZ]
+    plt.plot(HZ, exc, marker="o", ms=3, label=f"{pair} dir={d:+d} (n={len(g)})")
+plt.axhline(0, color="k", lw=.8)
+plt.title(f"{SYM} ({YEAR}+) - extra-rendimento medio vs baseline (stesso regime)")
+plt.xlabel("giorni dopo l'incrocio"); plt.ylabel("extra-rendimento cumulato (%)")
+plt.legend(); plt.grid(alpha=.3); plt.tight_layout()
+os.makedirs(RESULTS, exist_ok=True)
+outp = os.path.join(RESULTS, f"trajectories_{SYM}_{YEAR}.png")
+plt.savefig(outp, dpi=130)
+print("salvato:", outp)
@@ -16,12 +16,14 @@ input bool     InpAllHistory = true;            // true = tutto lo storico D1
 input datetime InpStart      = D'2010.01.01';   // inizio intervallo (se AllHistory=false)
 input datetime InpEnd        = D'2100.01.01';   // fine intervallo (se AllHistory=false)
 input string   InpFileName   = "";              // nome file ("" = automatico)
+input bool     InpBaseline   = true;            // crea anche il file baseline (tutte le barre D1)

 //--- costanti (stesse 7 MA dell'indicatore)
 #define ANCHOR_TF PERIOD_D1
 #define NSER 9          // PRICE, MED, MA365..MA3
-#define KSLOPE 5        // barre per pendenza / variazione cluster
-#define MAXH  20        // orizzonte massimo per gli esiti
+#define KSLOPE 5        // barre D1 per velocita'/accelerazione
+#define NVOL   14       // barre D1 per la volatilita'
+#define MAXH   20       // orizzonte massimo per gli esiti

 int    gDays[7] = {365,182,121,30,14,7,3};
 string SER[NSER]= {"PRICE","MED","MA365","MA182","MA121","MA30","MA14","MA7","MA3"};
@@ -53,6 +55,61 @@ double Median7(double &v[])   // mediana dei valori validi in v[0..6]
   return 0.5*(a[c/2-1]+a[c/2]);
  }

+//+------------------------------------------------------------------+
+// mediana dei primi c valori di src
+double MedArr(double &src[],int c)
+  {
+   if(c<=0) return 0;
+   double a[]; ArrayResize(a,c);
+   for(int j=0;j<c;j++) a[j]=src[j];
+   ArraySort(a);
+   if((c&1)==1) return a[c/2];
+   return 0.5*(a[c/2-1]+a[c/2]);
+  }
+
+//+------------------------------------------------------------------+
+// Velocita' = mediana delle 7 pendenze (variazione % di ogni MA su K barre D1)
+double VelMed(const double &S[][NSER],int i,int K)
+  {
+   double v[7]; int c=0;
+   for(int m=0;m<7;m++)
+     { double a=S[i][2+m], b=S[i-K][2+m]; if(IsVal(a)&&IsVal(b)) v[c++]=(a-b)/b*100.0; }
+   return MedArr(v,c);
+  }
+
+//+------------------------------------------------------------------+
+// Accelerazione = mediana delle 7 seconde differenze (cambio di pendenza)
+double AccMed(const double &S[][NSER],int i,int K)
+  {
+   double v[7]; int c=0;
+   for(int m=0;m<7;m++)
+     {
+      double a=S[i][2+m], b=S[i-K][2+m], d=S[i-2*K][2+m];
+      if(IsVal(a)&&IsVal(b)&&IsVal(d)) v[c++]=(a-2.0*b+d)/d*100.0;
+     }
+   return MedArr(v,c);
+  }
+
+//+------------------------------------------------------------------+
+// Volatilita' = mediana delle 7 dev.std dei rendimenti giornalieri di ogni MA su N barre
+double VolMed(const double &S[][NSER],int i,int N)
+  {
+   double v[7]; int c=0;
+   for(int m=0;m<7;m++)
+     {
+      double r[]; int rc=0; ArrayResize(r,N);
+      for(int t=i-N+1;t<=i;t++)
+        { double a=S[t][2+m], b=S[t-1][2+m]; if(IsVal(a)&&IsVal(b)) r[rc++]=(a-b)/b*100.0; }
+      if(rc>=2)
+        {
+         double mean=0; for(int j=0;j<rc;j++) mean+=r[j]; mean/=rc;
+         double s=0;    for(int j=0;j<rc;j++){ double dd=r[j]-mean; s+=dd*dd; }
+         v[c++]=MathSqrt(s/(rc-1));
+        }
+     }
+   return MedArr(v,c);
+  }
+
 //+------------------------------------------------------------------+
 void OnStart()
  {
@@ -60,7 +117,7 @@ void OnStart()
   if(!SymbolSelect(sym,true)) { Print("Simbolo non valido: ",sym); return; }
   int digits = (int)SymbolInfoInteger(sym,SYMBOL_DIGITS);

-   //--- handle delle 7 MA su D1 + ATR
+   //--- handle delle 7 MA su D1 (volatilita'/accelerazione calcolate dalle MA, no ATR di MT5)
   int hMA[7];
   for(int m=0;m<7;m++)
     {
@@ -68,33 +125,30 @@ void OnStart()
      hMA[m]  = iMA(sym,ANCHOR_TF,per,0,MODE_SMA,PRICE_CLOSE);
      if(hMA[m]==INVALID_HANDLE) { Print("iMA fallita m=",m); return; }
     }
-   int hATR = iATR(sym,ANCHOR_TF,14);
-   if(hATR==INVALID_HANDLE) { Print("iATR fallita"); return; }
+   int LB = MathMax(2*KSLOPE,NVOL);   // lookback necessario per vel/acc/vol

   //--- attendo che lo storico D1 sia pronto
   int total=0;
   for(int t=0; t<100; t++)
     {
      total = Bars(sym,ANCHOR_TF);
-      bool ok = (total>MAXH+KSLOPE+50);
+      bool ok = (total>MAXH+LB+50);
      for(int m=0;m<7 && ok;m++) if(BarsCalculated(hMA[m])<total) ok=false;
-      if(ok && BarsCalculated(hATR)>=total) break;
+      if(ok) break;
      Sleep(100);
     }
   total = Bars(sym,ANCHOR_TF);
-   if(total<=MAXH+KSLOPE+50) { Print("Storico D1 insufficiente: ",total," barre"); return; }
+   if(total<=MAXH+LB+50) { Print("Storico D1 insufficiente: ",total," barre"); return; }

   //--- carico tutta la storia D1 (indice 0 = piu' vecchio)
-   datetime tm[]; double cl[],hi[],lo[],atr[];
+   datetime tm[]; double cl[],hi[],lo[];
   MABuf ma[7];
   ArraySetAsSeries(tm,false); ArraySetAsSeries(cl,false);
   ArraySetAsSeries(hi,false); ArraySetAsSeries(lo,false);
-   ArraySetAsSeries(atr,false);
   if(CopyTime(sym,ANCHOR_TF,0,total,tm)<=0)  { Print("CopyTime KO");  return; }
   if(CopyClose(sym,ANCHOR_TF,0,total,cl)<=0) { Print("CopyClose KO"); return; }
   if(CopyHigh(sym,ANCHOR_TF,0,total,hi)<=0)  { Print("CopyHigh KO");  return; }
   if(CopyLow(sym,ANCHOR_TF,0,total,lo)<=0)   { Print("CopyLow KO");   return; }
-   if(CopyBuffer(hATR,0,0,total,atr)<=0)      { Print("CopyATR KO");   return; }
   for(int m=0;m<7;m++)
     {
      ArraySetAsSeries(ma[m].v,false);
@@ -117,8 +171,8 @@ void OnStart()
   //--- intervallo di scansione (eventi)
   datetime from = InpAllHistory ? 0          : InpStart;
   datetime to   = InpAllHistory ? TimeCurrent(): InpEnd;
-   int iStart = KSLOPE+1, iEnd = n-1;
-   for(int i=KSLOPE+1;i<n;i++) if(tm[i]>=from) { iStart=i; break; }
+   int iStart = LB+1, iEnd = n-1;
+   for(int i=LB+1;i<n;i++) if(tm[i]>=from) { iStart=i; break; }
   for(int i=n-1;i>=0;i--)     if(tm[i]<=to)    { iEnd=i;   break; }

   //--- apro il file CSV
@@ -128,7 +182,7 @@ void OnStart()

   //--- header
   string head = "time,symbol,pair,a,b,dir,price,med,ma365,ma182,ma121,ma30,ma14,ma7,ma3,"
-                 "dist_med_pct,cluster_pct,cluster_exp,slope_a,slope_b,trend,atr_pct,dow,month";
+                 "dist_med_pct,cluster_pct,cluster_exp,slope_a,slope_b,trend,vel_med,acc_med,vol_med,dow,month";
   for(int hh=0;hh<5;hh++)
     {
      string s=IntegerToString(gHor[hh]);
@@ -138,16 +192,32 @@ void OnStart()
   head += ",bars_to_revert,disc_max_pct";
   FileWriteString(fh,head+"\r\n");

+   //--- file baseline (una riga per OGNI barra D1 valida): serve per il confronto
+   //    "extra-rendimento" = incrocio vs giorno qualunque nello stesso regime
+   int fhB = INVALID_HANDLE;
+   if(InpBaseline)
+     {
+      string bname = "PaPP_bars_"+sym+"_D1.csv";
+      fhB = FileOpen(bname,FILE_WRITE|FILE_TXT|FILE_ANSI);
+      if(fhB==INVALID_HANDLE) Print("FileOpen baseline KO: ",bname," err=",GetLastError());
+      else
+        {
+         string bh = "time,symbol,price,med,dist_med_pct,cluster_pct,cluster_exp,trend,vel_med,acc_med,vol_med,dow,month,bars_to_revert,disc_max_pct";
+         for(int b=1;b<=MAXH;b++) bh += ",cret_"+IntegerToString(b);
+         FileWriteString(fhB,bh+"\r\n");
+        }
+     }
+
   //--- scansione incroci
-   long rows=0;
+   long rows=0, brows=0;
   for(int i=iStart;i<=iEnd;i++)
     {
-      if(i<KSLOPE+1) continue;
+      if(i<LB+1) continue;

-      //--- esporto solo barre con TUTTE le 9 serie valide (cluster completo)
+      //--- esporto solo barre con TUTTE le 9 serie valide su tutto il lookback
      bool allok=true;
      for(int k=0;k<NSER && allok;k++)
-         if(!IsVal(S[i][k]) || !IsVal(S[i-1][k]) || !IsVal(S[i-KSLOPE][k])) allok=false;
+         if(!IsVal(S[i][k]) || !IsVal(S[i-1][k]) || !IsVal(S[i-LB][k])) allok=false;
      if(!allok) continue;

      double price=S[i][0], med=S[i][1], ma365=S[i][2];
@@ -162,9 +232,21 @@ void OnStart()
      double clusterP = (cmaxP-cminP)/S[i-KSLOPE][0]*100.0;
      double cluster_exp = cluster-clusterP;
      int    trend = (price>ma365)?1:-1;
-      double atr_pct = atr[i]/price*100.0;
+      //--- velocita'/accelerazione/volatilita': mediana delle 7 scale (no ATR di MT5)
+      double vel_med = VelMed(S,i,KSLOPE);
+      double acc_med = AccMed(S,i,KSLOPE);
+      double vol_med = VolMed(S,i,NVOL);
      MqlDateTime dt; TimeToStruct(tm[i],dt);

+      //--- traiettoria forward (rendimento cumulato a +1..+MAXH), calcolata una volta per barra
+      string bpath="";
+      for(int b=1;b<=MAXH;b++)
+        {
+         int iB=i+b;
+         if(iB>n-1) bpath += ",";
+         else       bpath += ","+DoubleToString((cl[iB]-cl[i])/cl[i]*100.0,5);
+        }
+
      //--- esito globale: ritorno alla Mediana entro MAXH
      int side = (price>med)?1:-1;
      int b2rev=-1; double discMax=0;
@@ -178,6 +260,22 @@ void OnStart()
         if(MathAbs(d)>MathAbs(discMax)) discMax=d;
        }

+      //--- riga baseline (barra qualunque, indipendente dagli incroci)
+      if(fhB!=INVALID_HANDLE)
+        {
+         string br = TimeToString(tm[i],TIME_DATE)+","+sym+","
+                     +DoubleToString(price,digits)+","+DoubleToString(med,digits)+","
+                     +DoubleToString(dist_med,5)+","+DoubleToString(cluster,5)+","
+                     +DoubleToString(cluster_exp,5)+","+IntegerToString(trend)+","
+                     +DoubleToString(vel_med,5)+","+DoubleToString(acc_med,5)+","
+                     +DoubleToString(vol_med,5)+","+IntegerToString(dt.day_of_week)+","
+                     +IntegerToString(dt.mon)+","
+                     +(b2rev>0?IntegerToString(b2rev):"")+","+DoubleToString(discMax,5)
+                     +bpath;
+         FileWriteString(fhB,br+"\r\n");
+         brows++;
+        }
+
      //--- controllo ogni coppia (a,b)
      for(int a=0;a<NSER;a++)
       for(int b=a+1;b<NSER;b++)
@@ -190,7 +288,7 @@ void OnStart()

          double slope_a = (S[i][a]-S[i-KSLOPE][a])/S[i-KSLOPE][a]*100.0;
          double slope_b = (S[i][b]-S[i-KSLOPE][b])/S[i-KSLOPE][b]*100.0;
-          double thr = 0.25*atr_pct;
+          double thr = 0.25*vol_med;

          string row = StringFormat("%s,%s,%sx%s,%s,%s,%d,",
                          TimeToString(tm[i],TIME_DATE),sym,SER[a],SER[b],SER[a],SER[b],dir);
@@ -199,7 +297,8 @@ void OnStart()
          row += DoubleToString(dist_med,5)+","+DoubleToString(cluster,5)+","
                 +DoubleToString(cluster_exp,5)+","+DoubleToString(slope_a,5)+","
                 +DoubleToString(slope_b,5)+","+IntegerToString(trend)+","
-                 +DoubleToString(atr_pct,5)+","+IntegerToString(dt.day_of_week)+","
+                 +DoubleToString(vel_med,5)+","+DoubleToString(acc_med,5)+","
+                 +DoubleToString(vol_med,5)+","+IntegerToString(dt.day_of_week)+","
                 +IntegerToString(dt.mon);

          //--- esiti per orizzonte
@@ -217,13 +316,7 @@ void OnStart()
             row += ","+DoubleToString(ret,5)+","+DoubleToString(mfe,5)+","
                    +DoubleToString(mae,5)+","+IntegerToString(dlab)+","+IntegerToString(rev);
            }
-          //--- traiettoria: rendimento cumulato a +1..+MAXH barre
-          for(int b=1;b<=MAXH;b++)
-            {
-             int iB=i+b;
-             if(iB>n-1) { row += ","; continue; }
-             row += ","+DoubleToString((cl[iB]-cl[i])/cl[i]*100.0,5);
-            }
+          row += bpath;   // traiettoria forward (uguale per ogni coppia di questa barra)
          row += ","+(b2rev>0?IntegerToString(b2rev):"")+","+DoubleToString(discMax,5);
          FileWriteString(fh,row+"\r\n");
          rows++;
@@ -232,10 +325,11 @@ void OnStart()
     }

   FileClose(fh);
+   if(fhB!=INVALID_HANDLE) FileClose(fhB);
   for(int m=0;m<7;m++) IndicatorRelease(hMA[m]);
-   IndicatorRelease(hATR);
   Comment("");
   PrintFormat("PaPP export COMPLETATO: %d incroci -> %s (cartella MQL5\\Files)",(int)rows,fname);
+   if(InpBaseline) PrintFormat("Baseline: %d barre -> PaPP_bars_%s_D1.csv",(int)brows,sym);
   Print("Periodo: ",TimeToString(tm[iStart])," -> ",TimeToString(tm[iEnd]));
  }
 //+------------------------------------------------------------------+
Author	SHA1	Message	Date
Pietro Giacobazzi	19c2e0ac72	PaPP v2: cartella Analisi (script, risultati, metodologia incroci) Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-06-17 07:40:41 +00:00
pietro1991-dot	2070d44ce6	Merge pull request #11 from pietro1991-dot/devin/1781678159-export-baseline PaPP v2 export: file baseline (tutte le barre D1) per extra-rendimento	2026-06-17 09:22:50 +02:00
pietro1991-dot	fe7af9b8e0	Merge pull request #16 from pietro1991-dot/devin/1781680179-panel-fallback Co-authored-by: Pietro Giacobazzi <giacobazzipietro@gmail.com> Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-06-17 09:12:08 +02:00
Pietro Giacobazzi	884354d67e	PaPP v2 export: vel/acc/vol calcolate dalle 7 medie (mediana delle scale), rimosso ATR di MT5 Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-06-17 06:50:24 +00:00
Pietro Giacobazzi	41a2324b0d	PaPP v2 export: aggiunge file baseline (tutte le barre D1 + traiettoria) per extra-rendimento vs giorno qualunque Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>	2026-06-17 06:36:24 +00:00