特徴量(ファクターの生成)

ta-libが必要(使えない可能性)

ta-libが使えなかったら，各自で実装

#特徴量を計算する関数を定義する
def calc_features(df):

   #dfの特定列を変数に代入
    open=df['op']#シリーズ型
    high=df['hi']
    low=df['lo']
    close=df['cl']
    volume=df['volume']

    #今のdfの全ての列を変数に代入
    orig_columns=df.columns

    hilo=(df['hi']+df['lo'])/2 #足の中央値
   
    #インジケータの列を新規作成
    #ボリンジャーバンド
    df['BBANDS_upperband'],df['BBANDS_middleband'],df['BBANDS_lowerband']=talib.BBANDS(close,timeperiod=5,nbdevup=2,nbdevdn=2,matype=0)
    df['BBANDS_upperband'] -= hilo #hilo(足の中央値)を引いて上下片側のみの値にする。
    df['BBANDS_middleband'] -= hilo
    df['BBANDS_lowerband'] -= hilo
    df['DEMA'] = talib.DEMA(close, timeperiod=30) - hilo # 二重指数移動平均
    df['EMA'] = talib.EMA(close, timeperiod=30) - hilo #イドウヘイキン
    df['HT_TRENDLINE'] = talib.HT_TRENDLINE(close) - hilo
    df['KAMA'] = talib.KAMA(close, timeperiod=30) - hilo #Kaufmanの適応型移動平均
    df['MA'] = talib.MA(close, timeperiod=30, matype=0) - hilo
    df['MIDPOINT'] = talib.MIDPOINT(close, timeperiod=14) - hilo
    df['SMA'] = talib.SMA(close, timeperiod=30) - hilo
    df['T3'] = talib.T3(close, timeperiod=5, vfactor=0) - hilo
    df['TEMA'] = talib.TEMA(close, timeperiod=30) - hilo
    df['TRIMA'] = talib.TRIMA(close, timeperiod=30) - hilo
    df['WMA'] = talib.WMA(close, timeperiod=30) - hilo
   
    df['ADX'] = talib.ADX(high, low, close, timeperiod=14)
    df['ADXR'] = talib.ADXR(high, low, close, timeperiod=14)
    df['APO'] = talib.APO(close, fastperiod=12, slowperiod=26, matype=0)
    df['AROON_aroondown'], df['AROON_aroonup'] = talib.AROON(high, low, timeperiod=14)
    df['AROONOSC'] = talib.AROONOSC(high, low, timeperiod=14)
    df['BOP'] = talib.BOP(open, high, low, close)
    df['CCI'] = talib.CCI(high, low, close, timeperiod=14)
    df['DX'] = talib.DX(high, low, close, timeperiod=14)
    df['MACD_macd'], df['MACD_macdsignal'], df['MACD_macdhist'] = talib.MACD(close, fastperiod=12, slowperiod=26, signalperiod=9)
    # skip MACDEXT MACDFIX たぶん同じなので
    df['MFI'] = talib.MFI(high, low, close, volume, timeperiod=14)
    df['MINUS_DI'] = talib.MINUS_DI(high, low, close, timeperiod=14)
    df['MINUS_DM'] = talib.MINUS_DM(high, low, timeperiod=14)
    df['MOM'] = talib.MOM(close, timeperiod=10)
    df['PLUS_DI'] = talib.PLUS_DI(high, low, close, timeperiod=14)
    df['PLUS_DM'] = talib.PLUS_DM(high, low, timeperiod=14)
    df['RSI'] = talib.RSI(close, timeperiod=14)
    df['STOCH_slowk'], df['STOCH_slowd'] = talib.STOCH(high, low, close, fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)
    df['STOCHF_fastk'], df['STOCHF_fastd'] = talib.STOCHF(high, low, close, fastk_period=5, fastd_period=3, fastd_matype=0)
    df['STOCHRSI_fastk'], df['STOCHRSI_fastd'] = talib.STOCHRSI(close, timeperiod=14, fastk_period=5, fastd_period=3, fastd_matype=0)
    df['TRIX'] = talib.TRIX(close, timeperiod=30)
    df['ULTOSC'] = talib.ULTOSC(high, low, close, timeperiod1=7, timeperiod2=14, timeperiod3=28)
   
    df['WILLR'] = talib.WILLR(high, low, close, timeperiod=14)
    df['AD'] = talib.AD(high, low, close, volume)
    df['ADOSC'] = talib.ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10)
    df['OBV'] = talib.OBV(close, volume)
   
    df['ATR'] = talib.ATR(high, low, close, timeperiod=14)
    df['NATR'] = talib.NATR(high, low, close, timeperiod=14)
    df['TRANGE'] = talib.TRANGE(high, low, close)
   
    df['HT_DCPERIOD'] = talib.HT_DCPERIOD(close)
    df['HT_DCPHASE'] = talib.HT_DCPHASE(close)
    df['HT_PHASOR_inphase'], df['HT_PHASOR_quadrature'] = talib.HT_PHASOR(close)
    df['HT_SINE_sine'], df['HT_SINE_leadsine'] = talib.HT_SINE(close)
    df['HT_TRENDMODE'] = talib.HT_TRENDMODE(close)
   
    df['BETA'] = talib.BETA(high, low, timeperiod=5)
    df['CORREL'] = talib.CORREL(high, low, timeperiod=30)
    df['LINEARREG'] = talib.LINEARREG(close, timeperiod=14) - close
    df['LINEARREG_ANGLE'] = talib.LINEARREG_ANGLE(close, timeperiod=14)
    df['LINEARREG_INTERCEPT'] = talib.LINEARREG_INTERCEPT(close, timeperiod=14) - close
    df['LINEARREG_SLOPE'] = talib.LINEARREG_SLOPE(close, timeperiod=14)
    df['STDDEV'] = talib.STDDEV(close, timeperiod=5, nbdev=1)
    return df