refactor: Git에서 데이터 제거, 설정·코드만 유지

파이프라인 산출물(data/, docs/)을 Git 추적에서 제외하고
히스토리를 단일 커밋으로 재구성해 저장소 용량을 경량화한다.

Co-authored-by: Cursor <cursoragent@cursor.com>

src/deepcoin/techniques/pivot_points.py

@@ -0,0 +1,60 @@
+"""롤링 피벗 포인트 반등 기법."""
+
+from __future__ import annotations
+
+import pandas as pd
+
+from deepcoin.techniques.base import BaseTechnique, TechniqueParams, TechniqueSignal
+from deepcoin.techniques.helpers import make_signal
+from deepcoin.techniques.indicators import rolling_pivot_points
+
+
+class PivotPointsTechnique(BaseTechnique):
+    """S1 지지 반등 매수, R1 저항 거부 매도."""
+
+    technique_id = "pivot_points"
+    technique_name = "피벗 포인트"
+    category = "structure"
+    causal = True
+    description = "롤링 피벗 S1/R1 반전"
+
+    def default_extra_params(self) -> dict:
+        return {"window": 60, "touch_pct": 0.2}
+
+    def generate_signals(self, df: pd.DataFrame, params: TechniqueParams) -> list[TechniqueSignal]:
+        window = int(params.extra.get("window", 60))
+        touch_pct = float(params.extra.get("touch_pct", 0.2)) / 100.0
+
+        high = df["high"].astype(float)
+        low = df["low"].astype(float)
+        close = df["close"].astype(float)
+        _, s1, r1 = rolling_pivot_points(high, low, close, window=window)
+
+        signals: list[TechniqueSignal] = []
+        touched_s1 = False
+        touched_r1 = False
+
+        for i in range(window + 1, len(df)):
+            if pd.isna(s1.iloc[i]) or pd.isna(r1.iloc[i]):
+                continue
+
+            c = float(close.iloc[i])
+            l = float(low.iloc[i])
+            h = float(high.iloc[i])
+            s1_i = float(s1.iloc[i])
+            r1_i = float(r1.iloc[i])
+            prev_c = float(close.iloc[i - 1])
+
+            if l <= s1_i * (1 + touch_pct):
+                touched_s1 = True
+            if touched_s1 and prev_c <= s1_i and c > s1_i:
+                signals.append(make_signal(df, i, c, "buy", "pivot_s1_bounce", confidence=0.67))
+                touched_s1 = False
+
+            if h >= r1_i * (1 - touch_pct):
+                touched_r1 = True
+            if touched_r1 and prev_c >= r1_i and c < r1_i:
+                signals.append(make_signal(df, i, c, "sell", "pivot_r1_reject", confidence=0.67))
+                touched_r1 = False
+
+        return signals