ビットコインの未来の値段はわかる？「予測オシレーター」作戦を調べてみた！

"""
Forecast Oscillator Trading Signal
予測オシレーターによるトレンド判定
"""
import pandas as pd
import numpy as np


def calculate_forecast_oscillator_signals(df: pd.DataFrame,
                                        period: int = 14) -> pd.DataFrame:
    """
    Forecast Oscillator戦略のシグナル生成
    
    Parameters:
    -----------
    df : pd.DataFrame
        OHLCVデータ
    period : int
        計算期間（デフォルト: 14）
    
    Returns:
    --------
    pd.DataFrame
        シグナルが追加されたDataFrame
    """
    df = df.copy()
    
    # 線形回帰予測
    def linear_regression_forecast(data):
        if len(data) < 2:
            return np.nan
        x = np.arange(len(data))
        coeffs = np.polyfit(x, data, 1)
        return coeffs[0] * len(data) + coeffs[1]
    
    # 予測値
    df['forecast'] = df['close'].rolling(window=period).apply(linear_regression_forecast, raw=False)
    
    # Forecast Oscillator
    df['fosc'] = ((df['close'] - df['forecast']) / df['close']) * 100
    
    # シグナルライン
    df['fosc_signal'] = df['fosc'].rolling(window=3).mean()
    
    # シグナル初期化
    df['signal'] = 0
    df['is_buy'] = False
    df['is_sell'] = False
    
    position = 0
    
    for i in range(period + 3, len(df)):
        # 買いシグナル
        if position <= 0 and df['fosc'].iloc[i] > df['fosc_signal'].iloc[i] and df['fosc'].iloc[i] > 0:
            df.loc[df.index[i], 'is_buy'] = True
            df.loc[df.index[i], 'signal'] = 1
            position = 1
            
        # 売りシグナル
        elif position >= 0 and df['fosc'].iloc[i] < df['fosc_signal'].iloc[i] and df['fosc'].iloc[i] < 0:
            df.loc[df.index[i], 'is_sell'] = True
            df.loc[df.index[i], 'signal'] = -1
            position = -1
        else:
            df.loc[df.index[i], 'signal'] = position
    
    df['signal'] = df['signal'].fillna(0)
    
    return df


def get_strategy_name() -> str:
    """戦略名を返す"""
    return "Forecast Oscillator"


def get_strategy_description() -> str:
    """戦略の説明を返す"""
    return "予測オシレーターによるトレンド判定戦略"