moen0
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
def find_fvgs(candles, min_gap_size=0.0, impulse_multiplier=0.0):
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"""
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Find Fair Value Gaps in candle data.
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Args:
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candles: list of Candle objects
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min_gap_size: minimum gap size in price units to filter noise (0 = no filter)
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impulse_multiplier: minimum body-to-avg ratio for the middle candle (0 = no filter)
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"""
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fvgs = []
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avg_body = 0
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if impulse_multiplier > 0 and len(candles) > 20:
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bodies = [abs(c.close - c.open) for c in candles[:20]]
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avg_body = sum(bodies) / len(bodies)
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for i in range(2, len(candles)):
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c1 = candles[i - 2]
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c2 = candles[i - 1]
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c3 = candles[i]
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# Impulse check on middle candle
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if impulse_multiplier > 0 and avg_body > 0:
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middle_body = abs(c2.close - c2.open)
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if middle_body < avg_body * impulse_multiplier:
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continue
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# Update rolling average
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avg_body = (avg_body * 19 + middle_body) / 20
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# Bullish FVG
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if c1.high < c3.low:
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gap_size = c3.low - c1.high
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if gap_size >= min_gap_size:
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fvgs.append({
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"index": i - 1,
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"type": "bullish",
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"top": c3.low,
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"bottom": c1.high,
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"mitigated": False,
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})
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# Bearish FVG
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elif c1.low > c3.high:
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gap_size = c1.low - c3.high
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if gap_size >= min_gap_size:
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fvgs.append({
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"index": i - 1,
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"type": "bearish",
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"top": c1.low,
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"bottom": c3.high,
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"mitigated": False,
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})
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# Mark mitigated FVGs
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for fvg in fvgs:
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if fvg["mitigated"]:
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continue
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if fvg["type"] == "bullish":
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if c3.low <= fvg["bottom"]:
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fvg["mitigated"] = True
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elif fvg["type"] == "bearish":
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if c3.high >= fvg["top"]:
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fvg["mitigated"] = True
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return fvgs
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