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파이프라인 산출물(data/, docs/)을 Git 추적에서 제외하고 히스토리를 단일 커밋으로 재구성해 저장소 용량을 경량화한다. Co-authored-by: Cursor <cursoragent@cursor.com>
61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
"""롤링 피벗 포인트 반등 기법."""
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from __future__ import annotations
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import pandas as pd
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from deepcoin.techniques.base import BaseTechnique, TechniqueParams, TechniqueSignal
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from deepcoin.techniques.helpers import make_signal
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from deepcoin.techniques.indicators import rolling_pivot_points
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class PivotPointsTechnique(BaseTechnique):
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"""S1 지지 반등 매수, R1 저항 거부 매도."""
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technique_id = "pivot_points"
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technique_name = "피벗 포인트"
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category = "structure"
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causal = True
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description = "롤링 피벗 S1/R1 반전"
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def default_extra_params(self) -> dict:
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return {"window": 60, "touch_pct": 0.2}
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def generate_signals(self, df: pd.DataFrame, params: TechniqueParams) -> list[TechniqueSignal]:
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window = int(params.extra.get("window", 60))
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touch_pct = float(params.extra.get("touch_pct", 0.2)) / 100.0
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high = df["high"].astype(float)
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low = df["low"].astype(float)
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close = df["close"].astype(float)
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_, s1, r1 = rolling_pivot_points(high, low, close, window=window)
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signals: list[TechniqueSignal] = []
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touched_s1 = False
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touched_r1 = False
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for i in range(window + 1, len(df)):
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if pd.isna(s1.iloc[i]) or pd.isna(r1.iloc[i]):
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continue
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c = float(close.iloc[i])
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l = float(low.iloc[i])
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h = float(high.iloc[i])
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s1_i = float(s1.iloc[i])
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r1_i = float(r1.iloc[i])
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prev_c = float(close.iloc[i - 1])
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if l <= s1_i * (1 + touch_pct):
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touched_s1 = True
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if touched_s1 and prev_c <= s1_i and c > s1_i:
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signals.append(make_signal(df, i, c, "buy", "pivot_s1_bounce", confidence=0.67))
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touched_s1 = False
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if h >= r1_i * (1 - touch_pct):
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touched_r1 = True
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if touched_r1 and prev_c >= r1_i and c < r1_i:
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signals.append(make_signal(df, i, c, "sell", "pivot_r1_reject", confidence=0.67))
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touched_r1 = False
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return signals
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