dsyoon
741c949470
파이프라인 산출물(data/, docs/)을 Git 추적에서 제외하고 히스토리를 단일 커밋으로 재구성해 저장소 용량을 경량화한다. Co-authored-by: Cursor <cursoragent@cursor.com>
72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
"""RSI 다이버전스 기법."""
|
|
|
|
from __future__ import annotations
|
|
|
|
import pandas as pd
|
|
|
|
from deepcoin.techniques.base import BaseTechnique, TechniqueParams, TechniqueSignal
|
|
from deepcoin.techniques.helpers import (
|
|
dedupe_signals,
|
|
detect_bearish_divergence,
|
|
detect_bullish_divergence,
|
|
find_confirmed_pivots,
|
|
make_signal,
|
|
)
|
|
from deepcoin.techniques.indicators import rsi
|
|
|
|
|
|
class RsiDivergenceTechnique(BaseTechnique):
|
|
"""RSI 상승·하락 다이버전스 매수·매도."""
|
|
|
|
technique_id = "rsi_divergence"
|
|
technique_name = "RSI 다이버전스"
|
|
category = "divergence"
|
|
causal = True
|
|
description = "RSI 상승(Bd)·하락(Sd) 다이버전스"
|
|
|
|
def default_extra_params(self) -> dict:
|
|
return {"period": 14, "order": 12, "min_bars_between": 15, "max_bars_between": 400}
|
|
|
|
def generate_signals(self, df: pd.DataFrame, params: TechniqueParams) -> list[TechniqueSignal]:
|
|
period = int(params.extra.get("period", 14))
|
|
order = int(params.extra.get("order", 12))
|
|
min_bars = int(params.extra.get("min_bars_between", 15))
|
|
max_bars = int(params.extra.get("max_bars_between", 400))
|
|
|
|
close = df["close"].astype(float)
|
|
low = df["low"].astype(float)
|
|
high = df["high"].astype(float)
|
|
rsi_vals = rsi(close, period=period)
|
|
|
|
low_pivots = find_confirmed_pivots(low, order, "low")
|
|
high_pivots = find_confirmed_pivots(high, order, "high")
|
|
signals: list[TechniqueSignal] = []
|
|
|
|
for pivot_idx, _ in detect_bullish_divergence(
|
|
low_pivots, rsi_vals, min_bars_between=min_bars, max_bars_between=max_bars,
|
|
):
|
|
confirm_idx = pivot_idx + order
|
|
if confirm_idx >= len(df):
|
|
continue
|
|
signals.append(
|
|
make_signal(
|
|
df, confirm_idx, float(close.iloc[confirm_idx]), "buy",
|
|
"rsi_bull_divergence", pivot_bar_index=pivot_idx, confidence=0.78,
|
|
)
|
|
)
|
|
|
|
for pivot_idx, _ in detect_bearish_divergence(
|
|
high_pivots, rsi_vals, min_bars_between=min_bars, max_bars_between=max_bars,
|
|
):
|
|
confirm_idx = pivot_idx + order
|
|
if confirm_idx >= len(df):
|
|
continue
|
|
signals.append(
|
|
make_signal(
|
|
df, confirm_idx, float(close.iloc[confirm_idx]), "sell",
|
|
"rsi_bear_divergence", pivot_bar_index=pivot_idx, confidence=0.78,
|
|
)
|
|
)
|
|
|
|
return dedupe_signals(signals, min_bars=min_bars)
|