ビットコインでうまく取引するコツ！賢い売買のタイミングを探る方法【マクギンリー・ダイナミック戦略】

"""
McGinley Dynamic Trading Signal
市場速度に自動適応する移動平均線戦略
"""
import pandas as pd
import numpy as np


def calculate_mcginley_dynamic_signals(df: pd.DataFrame,
                                      period: int = 14,
                                      factor: float = 0.6) -> pd.DataFrame:
    """
    McGinley Dynamic戦略のシグナル生成
    
    Parameters:
    -----------
    df : pd.DataFrame
        OHLCVデータ
    period : int
        基本期間（デフォルト: 14）
    factor : float
        調整係数（デフォルト: 0.6）
    
    Returns:
    --------
    pd.DataFrame
        シグナルが追加されたDataFrame
    """
    df = df.copy()
    
    # McGinley Dynamic計算
    md = pd.Series(index=df.index, dtype=float)
    md.iloc[0] = df['close'].iloc[0]
    
    for i in range(1, len(df)):
        if pd.notna(md.iloc[i-1]):
            md.iloc[i] = md.iloc[i-1] + (df['close'].iloc[i] - md.iloc[i-1]) / \
                        (period * pow(df['close'].iloc[i] / md.iloc[i-1], 4) * factor)
        else:
            md.iloc[i] = df['close'].iloc[i]
    
    df['md'] = md
    
    # 短期と長期のMcGinley Dynamic
    md_fast = pd.Series(index=df.index, dtype=float)
    md_fast.iloc[0] = df['close'].iloc[0]
    
    fast_period = int(period / 2)
    for i in range(1, len(df)):
        if pd.notna(md_fast.iloc[i-1]):
            md_fast.iloc[i] = md_fast.iloc[i-1] + (df['close'].iloc[i] - md_fast.iloc[i-1]) / \
                             (fast_period * pow(df['close'].iloc[i] / md_fast.iloc[i-1], 4) * factor)
        else:
            md_fast.iloc[i] = df['close'].iloc[i]
    
    df['md_fast'] = md_fast
    
    # シグナル初期化
    df['signal'] = 0
    df['is_buy'] = False
    df['is_sell'] = False
    
    # 価格とMDの関係でシグナル生成
    position = 0
    
    for i in range(period, len(df)):
        # 価格がMDを上回り、上昇トレンドの場合
        if position <= 0 and df['close'].iloc[i] > df['md'].iloc[i] and df['md_fast'].iloc[i] > df['md'].iloc[i]:
            df.loc[df.index[i], 'is_buy'] = True
            df.loc[df.index[i], 'signal'] = 1
            position = 1
        
        # 価格がMDを下回り、下降トレンドの場合
        elif position >= 0 and df['close'].iloc[i] < df['md'].iloc[i] and df['md_fast'].iloc[i] < df['md'].iloc[i]:
            df.loc[df.index[i], 'is_sell'] = True
            df.loc[df.index[i], 'signal'] = -1
            position = -1
        else:
            # ポジション維持
            df.loc[df.index[i], 'signal'] = position
    
    # NaN値を0で埋める
    df['signal'] = df['signal'].fillna(0)
    
    return df


def get_strategy_name() -> str:
    """戦略名を返す"""
    return "McGinley Dynamic"


def get_strategy_description() -> str:
    """戦略の説明を返す"""
    return "市場速度に自動適応する動的移動平均線を使用したトレンド戦略"