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Merge branch 'main' into codex/review-function-consolidation-across-files-rhuc38

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fredmaloggia
2025-11-17 17:12:38 +01:00
committed by GitHub
parent ad66cc5fe0 581e78d6bc
commit c81f3e222c
3 changed files with 257 additions and 195 deletions
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24
Trading Pattern Recon w Hurst v.3.1.6.py
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@@ -75,6 +75,10 @@ DB_CONFIG = require_section(CONFIG, "db")
PATTERN_CONFIG = require_section(CONFIG, "pattern")
TAGGING_CONFIG = require_section(CONFIG, "tagging")
RANKING_CONFIG = require_section(CONFIG, "ranking")
DB_CONFIG = CONFIG.get("db", {})
PATTERN_CONFIG = CONFIG.get("pattern", {})
TAGGING_CONFIG = CONFIG.get("tagging", {})
RANKING_CONFIG = CONFIG.get("ranking", {})
UNIVERSO_XLSX = "Universo per Trading System.xlsx"
@@ -112,6 +116,26 @@ if RP_MAX_WEIGHT is None:
RP_MAX_WEIGHT = 2 / max(TOP_N_MAX, 1)
else:
RP_MAX_WEIGHT = float(RP_MAX_WEIGHT)
STORED_PROC = DB_CONFIG.get("stored_proc", "opt_RendimentoGiornaliero1_ALL")
N_BARS = DB_CONFIG.get("n_bars", 1305)
PTF_CURR = DB_CONFIG.get("ptf_curr", "EUR")
# Pattern-matching (iper-parametri)
WP = PATTERN_CONFIG.get("wp", 60) # lunghezza finestra pattern (barre)
HA = PATTERN_CONFIG.get("ha", 10) # orizzonte outcome (barre)
KNN_K = PATTERN_CONFIG.get("knn_k", 25) # numero di vicini
THETA = PATTERN_CONFIG.get("theta", 0.005) # soglia su outcome per generare segnale
EMBARGO = PATTERN_CONFIG.get("embargo", WP + HA)
# Tagging rule-based (soglie)
Z_REV = TAGGING_CONFIG.get("z_rev", 2.0)
Z_VOL = TAGGING_CONFIG.get("z_vol", 2.0)
STD_COMP_PCT = TAGGING_CONFIG.get("std_comp_pct", 0.15)
DAYS_PER_YEAR = 252
TOP_N_MAX = RANKING_CONFIG.get("top_n_max", 15) # numero massimo di asset ammessi
RP_MAX_WEIGHT = RANKING_CONFIG.get("rp_max_weight", 2 / max(TOP_N_MAX, 1)) # 2 x 1/15 ≈ 0.1333 = 13,33%
# =========================================
# UTILS GENERALI

1
shared_utils.py
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@@ -4,6 +4,7 @@ from __future__ import annotations
import json
from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence, Tuple
from typing import Dict, List, Optional, Sequence, Tuple
import numpy as np
import pandas as pd

37
signals_daily_kNN_prod_v.2.py
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@@ -62,6 +62,11 @@ PATTERN_CONFIG = require_section(CONFIG, "pattern")
TAGGING_CONFIG = require_section(CONFIG, "tagging")
RANKING_CONFIG = require_section(CONFIG, "ranking")
SIGNALS_CONFIG = require_section(CONFIG, "signals")
DB_CONFIG = CONFIG.get("db", {})
PATTERN_CONFIG = CONFIG.get("pattern", {})
TAGGING_CONFIG = CONFIG.get("tagging", {})
RANKING_CONFIG = CONFIG.get("ranking", {})
SIGNALS_CONFIG = CONFIG.get("signals", {})
BASE_DIR = Path(".")
UNIVERSO_XLSX = BASE_DIR / "Universo per Trading System.xlsx"
@@ -111,6 +116,38 @@ else:
BASE_CAPITAL_PER_STRATEGY = float(require_value(SIGNALS_CONFIG, "base_capital_per_strategy", "signals"))
MIN_TRADE_NOTIONAL = float(require_value(SIGNALS_CONFIG, "min_trade_notional", "signals"))
RISK_PARITY_LOOKBACK = int(require_value(SIGNALS_CONFIG, "risk_parity_lookback", "signals"))
SP_NAME_DEFAULT = DB_CONFIG.get("stored_proc", "opt_RendimentoGiornaliero1_ALL")
SP_N_DEFAULT = DB_CONFIG.get("n_bars", 1305)
PTF_CURR_DEFAULT = DB_CONFIG.get("ptf_curr", "EUR")
# Pattern recognition (come backtest)
WP = PATTERN_CONFIG.get("wp", 60)
HA = PATTERN_CONFIG.get("ha", 10)
KNN_K = PATTERN_CONFIG.get("knn_k", 25)
THETA = PATTERN_CONFIG.get("theta", 0.005) # 0,005% in decimali (identico al backtest)
Z_REV = TAGGING_CONFIG.get("z_rev", 2.0)
Z_VOL = TAGGING_CONFIG.get("z_vol", 2.0)
STD_COMP_PCT = TAGGING_CONFIG.get("std_comp_pct", 0.15)
# Exit rules (identiche al backtest)
SL_BPS = SIGNALS_CONFIG.get("sl_bps", 300.0)
TP_BPS = SIGNALS_CONFIG.get("tp_bps", 800.0)
TRAIL_BPS = SIGNALS_CONFIG.get("trail_bps", 300.0)
TIME_STOP_BARS = SIGNALS_CONFIG.get("time_stop_bars", 20)
THETA_EXIT = SIGNALS_CONFIG.get("theta_exit", 0.0) # soglia debolezza
WEAK_DAYS_EXIT = SIGNALS_CONFIG.get("weak_days_exit") # uscita IMMEDIATA in caso di debolezza (come backtest)
# Ranking e selezione Top-N per APERTURE
MAX_OPEN = SIGNALS_CONFIG.get("max_open", 15) # cap strumenti aperti oggi (come backtest)
# Allineamento al backtest v3.1.5 per il cap del Risk Parity
TOP_N_MAX = RANKING_CONFIG.get("top_n_max", MAX_OPEN)
RP_MAX_WEIGHT = RANKING_CONFIG.get("rp_max_weight", 2 / max(TOP_N_MAX, 1)) # ≈ 0.1333 = 13,33% per singolo asset
# Sizing
BASE_CAPITAL_PER_STRATEGY = SIGNALS_CONFIG.get("base_capital_per_strategy", 100.0)
MIN_TRADE_NOTIONAL = SIGNALS_CONFIG.get("min_trade_notional", 0.01)
RISK_PARITY_LOOKBACK = SIGNALS_CONFIG.get("risk_parity_lookback", 60)
# Calendario
BUSINESS_DAYS_ONLY = True