marcotav

import numpy as np
import pandas as pd
import pandas_datareader as pdr
from statsmodels.tsa.stattools import adfuller
pd.core.common.is_list_like = pd.api.types.is_list_like
import matplotlib.pyplot as plt
from numpy import cumsum, log, polyfit, sqrt, std, subtract
from datetime import datetime
import time
%matplotlib inline

marcotav

import numpy as np
import matplotlib.pyplot as plt
from hurst import compute_Hc, random_walk
import seaborn as sns
sns.set();
%matplotlib inline
np.random.seed(42)
random_changes = 1. + np.random.randn(99999) / 1000.
series = np.cumprod(random_changes)  
H, c, result = compute_Hc(series, kind='price', simplified=True)

marcotav

import numpy as np
import pandas as pd
import pandas_datareader as pdr
from statsmodels.tsa.stattools import adfuller
pd.core.common.is_list_like = pd.api.types.is_list_like
import matplotlib.pyplot as plt
from datetime import datetime
import time
%matplotlib inline