渦巻きサインで未来の値段を予想！『Vortex Indicator』を使ってみた結果

#!/usr/bin/env python3
"""
Vortex Indicator戦略
トレンドの方向と強さを測定
"""
import pandas as pd
import numpy as np


def calculate_vortex_signals(df: pd.DataFrame, vi_period: int = 14) -> pd.DataFrame:
    """
    Vortex Indicatorシグナルを生成
    
    Parameters:
    -----------
    df : pd.DataFrame
        OHLCVデータ
    vi_period : int
        VI計算期間（デフォルト: 14）
    
    Returns:
    --------
    pd.DataFrame
        シグナル列が追加されたDataFrame
    """
    df = df.copy()
    
    # Vortex Movement計算
    df['vm_plus'] = np.abs(df['high'] - df['low'].shift(1))
    df['vm_minus'] = np.abs(df['low'] - df['high'].shift(1))
    
    # True Range
    df['tr'] = np.maximum(
        df['high'] - df['low'],
        np.abs(df['high'] - df['close'].shift(1)),
        np.abs(df['low'] - df['close'].shift(1))
    )
    
    # VI+ と VI- 計算
    df['vi_plus'] = df['vm_plus'].rolling(window=vi_period).sum() / df['tr'].rolling(window=vi_period).sum()
    df['vi_minus'] = df['vm_minus'].rolling(window=vi_period).sum() / df['tr'].rolling(window=vi_period).sum()
    
    # シグナル生成（VI+とVI-のクロス）
    df['is_buy'] = (
        (df['vi_plus'] > df['vi_minus']) & 
        (df['vi_plus'].shift(1) <= df['vi_minus'].shift(1))
    )
    
    df['is_sell'] = (
        (df['vi_plus'] < df['vi_minus']) & 
        (df['vi_plus'].shift(1) >= df['vi_minus'].shift(1))
    )
    
    # NaN値をFalseに置換
    df['is_buy'] = df['is_buy'].fillna(False)
    df['is_sell'] = df['is_sell'].fillna(False)
    
    print(f"Vortex Indicator: 期間={vi_period}")
    print(f"買いシグナル数: {df['is_buy'].sum()}")
    print(f"売りシグナル数: {df['is_sell'].sum()}")
    
    return df