목록STOCK/비트코인 (19)

데이터 공부를 기록하는 공간

백테스트 - MLP 5분봉 volume 변수추가

df = pd.read_csv("20220103_btc_minute5_90days.csv").rename(columns = {"Unnamed: 0":'datetime'}).set_index("datetime") df = df[['close','volume']] data = df.copy() data['return'] = np.log(data['close']/data['close'].shift(1)) data['volumeR'] = np.log(data['volume']/data['volume'].shift(1)) data.dropna(inplace=True) data['direction'] = np.where(data['return']>0, 1, 0) lags = 3 cols = [] for lag in..
STOCK/비트코인 2022. 1. 3. 01:46
백테스트 - MLP 5분봉

pred.sum()​ # df = pyupbit.get_ohlcv("KRW-BTC", "minute5", count=12*24*30*3) df = pd.read_csv("20220103_btc_minute5_90days.csv").rename(columns = {"Unnamed: 0":'datetime'}).set_index("datetime") df = df[['close','volume']] df data = df.copy() data['return'] = np.log(data['close']/data['close'].shift(1)) data.dropna(inplace=True) data['direction'] = np.where(data['return']>0, 1, 0) lags = 5 cols ..
STOCK/비트코인 2022. 1. 3. 01:23
백테스트 - MLP

(참고) 파이썬을 활용한 알고리즘 트레이딩 6장 data = df.copy() data['return'] = np.log(data['close']/data['close'].shift(1)) data.dropna(inplace=True) data['direction'] = np.where(data['return']>0, 1, 0) lags = 5 cols = [] for lag in range(1, lags+1): col = "lag_{}".format(lag) data[col] = data['return'].shift(lag) cols.append(col) data.dropna(inplace=True) data import tensorflow as tf from keras.models import Seq..
STOCK/비트코인 2022. 1. 3. 00:53
백테스트 - logistic regression

(참고) 파이썬을 이용한 알고리즘 트레이딩 5장 data = df.copy() data['return'] = np.log(data['close']/data['close'].shift(1)) data.dropna(inplace=True) lags = 3 cols = [] for lag in range(1, lags+1): col = "lag_{}".format(lag) data[col] = data['return'].shift(lag) cols.append(col) data.dropna(inplace=True) data from sklearn.metrics import accuracy_score from sklearn.linear_model import LogisticRegression lm = Logis..
STOCK/비트코인 2022. 1. 3. 00:03
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