mirror of
https://github.com/Sabermrddz/QuantCore-FX.git
synced 2026-08-15 03:38:05 +00:00
206 lines
7.9 KiB
Python
206 lines
7.9 KiB
Python
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from typing import Dict, List, Optional, Tuple
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from dataclasses import dataclass
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from datetime import datetime, timezone
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import statistics
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import config
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@dataclass
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class CurrencyStrength:
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name: str
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avg_z_score: float
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rank: int
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is_overbought: bool
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is_oversold: bool
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direction: str
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session_srv: float = 0.0 # Session Relative Velocity (Task 1.2)
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class SessionTracker:
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"""Detects the active trading session and tracks session-start snapshots.
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Sessions (UTC):
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Tokyo: 00:00–08:00
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London: 07:00–16:00
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New York: 13:00–22:00
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Overlapping hours are resolved as London (the dominant session).
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"""
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TOKYO = "Tokyo"
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LONDON = "London"
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NEWYORK = "New York"
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def __init__(self):
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self.current_session: Optional[str] = None
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self.session_start_prices: Dict[str, float] = {} # pair -> price at session open
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self.session_open_time: Optional[datetime] = None
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def get_active_session(self, utc_hour: int = None) -> str:
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if utc_hour is None:
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utc_hour = datetime.now(timezone.utc).hour
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if config.SESSION_LONDON_OPEN <= utc_hour < config.SESSION_LONDON_CLOSE:
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return self.LONDON
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if config.SESSION_TOKYO_OPEN <= utc_hour < config.SESSION_TOKYO_CLOSE:
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return self.TOKYO
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if config.SESSION_NEWYORK_OPEN <= utc_hour < config.SESSION_NEWYORK_CLOSE:
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return self.NEWYORK
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return "Off-Hours"
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def check_new_session(self, current_prices: Dict[str, float]) -> Optional[str]:
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"""Detect if a new session has started and snapshot prices."""
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now = datetime.now(timezone.utc)
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session = self.get_active_session(now.hour)
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if session != self.current_session and session != "Off-Hours":
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self.current_session = session
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self.session_start_prices = dict(current_prices)
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self.session_open_time = now
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return session
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if self.current_session is None:
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self.current_session = session
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if session != "Off-Hours":
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self.session_start_prices = dict(current_prices)
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self.session_open_time = now
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return None
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def compute_srv(self, pair: str, current_price: float) -> float:
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"""Session Relative Velocity: % change from session open to now."""
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start = self.session_start_prices.get(pair)
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if start is None or start == 0:
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return 0.0
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return ((current_price - start) / start) * 100.0
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class CurrencyStrengthMatrix:
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"""Computes individual currency strength indices from pair Z-scores.
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Includes Session-Based Indexing (Task 1.2):
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- Tracks performance since Tokyo/London/NY session opens
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- Session Relative Velocity (SRV) per currency
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"""
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def __init__(self, z_scores: Dict[str, float] = None):
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self.currencies = config.CURRENCIES
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self.threshold = config.Z_SCORE_THRESHOLD
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self._raw_scores: Dict[str, List[float]] = {}
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self._strengths: Dict[str, CurrencyStrength] = {}
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self.session_tracker = SessionTracker()
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self._srv_map: Dict[str, float] = {} # currency -> avg SRV
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if z_scores:
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self.update(z_scores)
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def update(self, z_scores: Dict[str, float], current_prices: Dict[str, float] = None):
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"""Recompute all currency strengths from 28 pair Z-scores.
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If current_prices is provided, also updates session tracking
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and computes Session Relative Velocity.
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"""
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self._raw_scores = {}
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for ccy in self.currencies:
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scores = []
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for other in self.currencies:
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if other == ccy:
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continue
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pair = f"{ccy}_{other}"
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z = z_scores.get(pair)
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if z is not None:
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scores.append(z)
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self._raw_scores[ccy] = scores
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strengths = {}
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for ccy, scores in self._raw_scores.items():
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avg_z = statistics.mean(scores) if scores else 0.0
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strengths[ccy] = CurrencyStrength(
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name=ccy,
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avg_z_score=avg_z,
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rank=0,
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is_overbought=avg_z >= self.threshold,
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is_oversold=avg_z <= -self.threshold,
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direction="OVERBOUGHT" if avg_z >= self.threshold else ("OVERSOLD" if avg_z <= -self.threshold else "NEUTRAL"),
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)
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sorted_ccys = sorted(strengths.keys(), key=lambda c: strengths[c].avg_z_score, reverse=True)
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for rank, ccy in enumerate(sorted_ccys, 1):
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strengths[ccy].rank = rank
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# Session tracking (Task 1.2)
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if current_prices:
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new_session = self.session_tracker.check_new_session(current_prices)
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self._compute_srv(current_prices, strengths)
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self._strengths = strengths
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def _compute_srv(self, current_prices: Dict[str, float],
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strengths: Dict[str, CurrencyStrength]):
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"""Compute average Session Relative Velocity per currency."""
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srv_scores: Dict[str, List[float]] = {c: [] for c in self.currencies}
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for ccy in self.currencies:
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for other in self.currencies:
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if other == ccy:
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continue
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pair = f"{ccy}_{other}"
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price = current_prices.get(pair)
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if price is not None:
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srv = self.session_tracker.compute_srv(pair, price)
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srv_scores[ccy].append(srv)
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for ccy in self.currencies:
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scores = srv_scores[ccy]
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self._srv_map[ccy] = statistics.mean(scores) if scores else 0.0
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if ccy in strengths:
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strengths[ccy].session_srv = self._srv_map[ccy]
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def get_strongest(self) -> Optional[CurrencyStrength]:
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return max(self._strengths.values(), key=lambda s: s.avg_z_score) if self._strengths else None
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def get_weakest(self) -> Optional[CurrencyStrength]:
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return min(self._strengths.values(), key=lambda s: s.avg_z_score) if self._strengths else None
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def get_matrix_cross(self) -> Optional[str]:
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s = self.get_strongest()
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w = self.get_weakest()
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if s and w and s.name != w.name:
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return f"{s.name}_{w.name}"
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return None
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def get_divergence_gap(self) -> float:
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s = self.get_strongest()
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w = self.get_weakest()
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return (s.avg_z_score - w.avg_z_score) if s and w else 0.0
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def has_divergence(self) -> bool:
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s = self.get_strongest()
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w = self.get_weakest()
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return bool(s and w and s.is_overbought and w.is_oversold)
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def get_strong_currencies(self) -> List[str]:
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return [c.name for c in self._strengths.values() if c.is_overbought]
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def get_weak_currencies(self) -> List[str]:
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return [c.name for c in self._strengths.values() if c.is_oversold]
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def get_ranked_list(self) -> List[CurrencyStrength]:
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return sorted(self._strengths.values(), key=lambda s: s.rank)
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def get_active_session(self) -> str:
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return self.session_tracker.get_active_session()
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def get_srv_map(self) -> Dict[str, float]:
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return dict(self._srv_map)
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def get_report(self) -> Dict:
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ranked = self.get_ranked_list()
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s = self.get_strongest()
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w = self.get_weakest()
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return {
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"ranked": [(c.name, round(c.avg_z_score, 2), c.direction, round(c.session_srv, 4)) for c in ranked],
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"strongest": s.name if s else None,
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"strongest_z": round(s.avg_z_score, 2) if s else 0,
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"weakest": w.name if w else None,
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"weakest_z": round(w.avg_z_score, 2) if w else 0,
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"matrix_cross": self.get_matrix_cross(),
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"divergence_gap": round(self.get_divergence_gap(), 2),
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"has_divergence": self.has_divergence(),
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"overbought": self.get_strong_currencies(),
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"oversold": self.get_weak_currencies(),
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"active_session": self.get_active_session(),
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}
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