moen0
263 lines
8.7 KiB
Python
263 lines
8.7 KiB
Python
from data.model import Signal
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from indicators.market_structure import find_swing_points, detect_structure
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from indicators.liquidity import find_liquidity_levels
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from indicators.fvg import find_fvgs
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from indicators.order_blocks import find_order_blocks
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from indicators.sessions import in_session, in_day_filter, get_asian_range, get_sessions_for_tz
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from collections import defaultdict
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class ICTStrategy:
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def __init__(
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self,
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lookback=5,
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atr_mult=1.5,
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session="new_york",
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use_fvg=True,
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use_ob=True,
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use_liquidity_sweep=True,
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ob_max_age=50,
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proximity_pct=0.3,
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sweep_lookback=10,
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min_gap_size=0.0,
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impulse_multiplier=0.0,
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require_unmitigated_fvg=True,
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require_bos_confluence=False,
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min_ob_size=0.0,
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require_fvg_ob_confluence=False,
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asian_sweep_only=False,
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day_filter=None,
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sl_buffer_pips=0.0005,
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use_break_even=False,
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be_trigger_rr=1.0,
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use_partial_tp=False,
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partial_tp_rr=1.0,
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partial_tp_percent=50.0,
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timezone="est",
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):
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self.lookback = lookback
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self.atr_mult = atr_mult
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self.session = session
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self.use_fvg = use_fvg
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self.use_ob = use_ob
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self.use_liquidity_sweep = use_liquidity_sweep
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self.ob_max_age = ob_max_age
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self.proximity_pct = proximity_pct
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self.sweep_lookback = sweep_lookback
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self.min_gap_size = min_gap_size
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self.impulse_multiplier = impulse_multiplier
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self.require_unmitigated_fvg = require_unmitigated_fvg
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self.require_bos_confluence = require_bos_confluence
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self.min_ob_size = min_ob_size
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self.require_fvg_ob_confluence = require_fvg_ob_confluence
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self.asian_sweep_only = asian_sweep_only
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self.day_filter = day_filter
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self.sl_buffer_pips = sl_buffer_pips
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self.use_break_even = use_break_even
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self.be_trigger_rr = be_trigger_rr
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self.use_partial_tp = use_partial_tp
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self.partial_tp_rr = partial_tp_rr
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self.partial_tp_percent = partial_tp_percent
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self.sessions_map = get_sessions_for_tz(timezone)
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self.swings = []
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self.structure = []
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self.fvgs = []
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self.order_blocks = []
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self.liquidity_levels = []
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self.asian_ranges = {}
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self.recent_sweep = None
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self.sweep_expiry = 0
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def prepare(self, candles):
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self.swings = find_swing_points(candles, self.lookback)
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self.structure = detect_structure(self.swings)
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self.fvgs = find_fvgs(
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candles,
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min_gap_size=self.min_gap_size,
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impulse_multiplier=self.impulse_multiplier,
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)
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self.order_blocks = find_order_blocks(
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candles,
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self.structure,
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min_ob_size=self.min_ob_size,
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)
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self.liquidity_levels = find_liquidity_levels(self.swings)
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daily = defaultdict(list)
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for c in candles:
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daily[c.time_open.date()].append(c)
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for date, day_candles in daily.items():
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ar = get_asian_range(day_candles, sessions_map=self.sessions_map)
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if ar:
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self.asian_ranges[date] = ar
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def get_bias(self, index):
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recent = [s for s in self.structure if s["index"] < index]
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if len(recent) < 2:
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return None
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last_two = recent[-2:]
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labels = [s["label"] for s in last_two]
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if "HH" in labels and "HL" in labels:
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return "bullish"
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if "LL" in labels and "LH" in labels:
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return "bearish"
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if labels[-1] in ("HH", "HL"):
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return "bullish"
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if labels[-1] in ("LL", "LH"):
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return "bearish"
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return None
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def _find_swing_sl(self, index, direction, candle):
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"""
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Long -> SL below most recent swing low
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Short -> SL above most recent swing high
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Fallback to atr_mult bracket if no valid swing found.
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"""
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target_type = "low" if direction == "BUY" else "high"
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for swing in reversed(self.swings):
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if swing["index"] >= index:
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continue
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if swing["type"] != target_type:
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continue
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if direction == "BUY":
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sl = swing["price"] - self.sl_buffer_pips
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if sl < candle.close:
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return sl
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else:
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sl = swing["price"] + self.sl_buffer_pips
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if sl > candle.close:
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return sl
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# Fallback
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bracket = (candle.high - candle.low) * self.atr_mult
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if direction == "BUY":
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return candle.close - bracket
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return candle.close + bracket
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def _has_recent_bos(self, index, direction):
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for s in reversed(self.structure):
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if s["index"] >= index:
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continue
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if s["index"] < index - 20:
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break
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if direction == "bullish" and s["label"] == "HH":
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return True
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if direction == "bearish" and s["label"] == "LL":
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return True
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return False
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def check_liquidity_sweep(self, candle, index):
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today = candle.time_open.date()
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ar = self.asian_ranges.get(today)
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if ar:
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if candle.high > ar["high"] and candle.close < ar["high"]:
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return "swept_high"
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if candle.low < ar["low"] and candle.close > ar["low"]:
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return "swept_low"
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if self.asian_sweep_only:
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return None
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for level in self.liquidity_levels:
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if level["type"] == "equal_highs":
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if candle.high > level["price"] and candle.close < level["price"]:
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return "swept_high"
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elif level["type"] == "equal_lows":
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if candle.low < level["price"] and candle.close > level["price"]:
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return "swept_low"
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return None
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def in_ob_zone(self, price, index):
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for ob in self.order_blocks:
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age = index - ob["index"]
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if 0 < age < self.ob_max_age:
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size = ob["top"] - ob["bottom"]
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buffer = max(size * 2, 0.05)
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if (ob["bottom"] - buffer) <= price <= (ob["top"] + buffer):
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return ob["type"]
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return None
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def in_fvg_zone(self, price, index):
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for fvg in self.fvgs:
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age = index - fvg["index"]
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if 0 < age < self.ob_max_age:
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if self.require_unmitigated_fvg and fvg.get("mitigated", False):
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continue
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size = fvg["top"] - fvg["bottom"]
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buffer = max(size * 2, 0.05)
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if (fvg["bottom"] - buffer) <= price <= (fvg["top"] + buffer):
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return fvg["type"]
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return None
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def check_signal(self, candles, index):
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"""Returns Signal or None."""
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if index < 4:
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return None
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candle = candles[index]
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if not in_session(candle.time_open, self.session, sessions_map=self.sessions_map):
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self.recent_sweep = None
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return None
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if not in_day_filter(candle.time_open, self.day_filter):
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return None
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bias = self.get_bias(index)
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if bias is None:
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return None
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sweep = self.check_liquidity_sweep(candle, index)
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if sweep:
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self.recent_sweep = sweep
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self.sweep_expiry = index + self.sweep_lookback
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if index > self.sweep_expiry:
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self.recent_sweep = None
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ob_zone = self.in_ob_zone(candle.close, index) if self.use_ob else None
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fvg_zone = self.in_fvg_zone(candle.close, index) if self.use_fvg else None
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if self.require_fvg_ob_confluence:
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if not (ob_zone and fvg_zone):
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ob_zone = None
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fvg_zone = None
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if self.require_bos_confluence:
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if not self._has_recent_bos(index, bias):
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return None
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direction = None
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if bias == "bullish":
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if self.use_liquidity_sweep and self.recent_sweep != "swept_low":
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return None
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if ob_zone == "bullish" or fvg_zone == "bullish":
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direction = "BUY"
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elif bias == "bearish":
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if self.use_liquidity_sweep and self.recent_sweep != "swept_high":
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return None
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if ob_zone == "bearish" or fvg_zone == "bearish":
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direction = "SELL"
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if direction is None:
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return None
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sl = self._find_swing_sl(index, direction, candle)
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return Signal(
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direction=direction,
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stop_loss=sl,
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entry_price=candle.close,
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) |