お金の流れを読んでみよう！仮想通貨の売買チャレンジ「チャイキン・マネーフロー」

#!/usr/bin/env python3
"""
Chaikin Money Flow (CMF)戦略
出来高加重の資金流入・流出を測定
"""
import pandas as pd
import numpy as np


def calculate_cmf_signals(df: pd.DataFrame, cmf_period: int = 20, 
                         threshold: float = 0.05) -> pd.DataFrame:
    """
    Chaikin Money Flowシグナルを生成
    
    Parameters:
    -----------
    df : pd.DataFrame
        OHLCVデータ
    cmf_period : int
        CMF計算期間（デフォルト: 20）
    threshold : float
        シグナル閾値（デフォルト: 0.05）
    
    Returns:
    --------
    pd.DataFrame
        シグナル列が追加されたDataFrame
    """
    df = df.copy()
    
    # Money Flow Multiplier計算
    df['mf_multiplier'] = ((df['close'] - df['low']) - (df['high'] - df['close'])) / (df['high'] - df['low'])
    df['mf_multiplier'] = df['mf_multiplier'].fillna(0)
    
    # Money Flow Volume
    df['mf_volume'] = df['mf_multiplier'] * df['volume']
    
    # Chaikin Money Flow
    df['cmf'] = (
        df['mf_volume'].rolling(window=cmf_period).sum() / 
        df['volume'].rolling(window=cmf_period).sum()
    )
    
    # CMFの変化率
    df['cmf_change'] = df['cmf'] - df['cmf'].shift(1)
    
    # シグナル生成
    df['is_buy'] = (
        (df['cmf'] > threshold) &  # CMFが正の閾値を超える
        (df['cmf'].shift(1) <= threshold) &  # 前期間は閾値以下
        (df['cmf_change'] > 0)  # CMFが上昇中
    )
    
    df['is_sell'] = (
        (df['cmf'] < -threshold) &  # CMFが負の閾値を下回る
        (df['cmf'].shift(1) >= -threshold) &  # 前期間は閾値以上
        (df['cmf_change'] < 0)  # CMFが下降中
    )
    
    # 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"Chaikin Money Flow: 期間={cmf_period}, 閾値={threshold}")
    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