backtesting.py | mag_right chart_with_upwards_trend snake | Cryptocurrency library

# pip install backtesting
from backtesting import Strategy

class StrategyParentClass:
    def __init__(self, whatever=True):
        self.whatever=whatever

class StrategyChildClass(StrategyParentClass, Strategy):
    def __init__(self):

CustomStrategy = ta.Strategy(
    name="Momo and Volatility",
    description="SMA 50,200, BBANDS, RSI, MACD and Volume SMA 20",
    ta=[
        {"kind": "sma", "length": 20},
        {"kind": "sma", "length": 60},
        {"kind": "bband

# Convert Date_buy to datetime
df['Date_buy'] = pd.to_datetime(df['Date_buy'])

df = df.set_index('Date_buy').resample('D').pad().reset_index()

>>> df
       Date_buy Name_buy
0    2003-05-14      TLT
1   

from sklearn.metrics import mean_absolute_error
from sklearn.metrics import mean_squared_error

def test_train_spl(data, testsize):

    test = data.tail(testsize)
    train = data.head(data.shape[0] - testsize)
    return test, train

correct = np.where( advice == real_choice
                     , "CORRECT", "INCORRECT)

df['correct'] = np.where( df['advice'] == df['real_choice']
                     , "CORRECT", "INCORRECT)

<

Long_frame = {'date':['2020-01-10', '2020-01-11', '2020-01-12', '2020-01-13', '2020-01-14', '2020-01-15'],'index': [2, 4, 6, 8, 10, 20]}
Short_frame = {'date':['2020-01-10', '2020-01-11', '2020-01-13', '2020-01-15'], 'index': [2, 4, 8, 20]

for i in range(0,rsibtc.shape[0]):
    if rsibtc['RSI'].iloc[i] < 70 and rsibtc['RSI'].iloc[i-1] > 70:
        Position.append('Short')
    elif rsibtc['RSI'].iloc[i] > 30 and rsibtc['RSI'].iloc[i-1] < 30:
        Position.appe

s=df.loc[df.entry_signal.cummax().astype(bool),'price'].pct_change().add(1).fillna(1)

df['trailing stop loss']=s.clip_lower(1).cumprod()*99
df['exit_signal']=(df['trailing stop loss']>df['price']).astype(int)
df
Out[114]: 
         dat