Hello! Just working with your code on a time series analysis, to compute the Hurst exponent of a equity, e.g. Google.
Here is the code:
import matplotlib.pyplot as plt
from hurst import compute_Hc
from datetime import datetime
import pandas_datareader as web
series = web.DataReader("GOOG", "yahoo", datetime(2000,1,1), datetime(2013,1,1))
H, c, data = compute_Hc(series['Adj Close'], kind='price', simplified=True)
Output: H 0.82083 C 0.5268
Following this resource for the Google stock a Hurst of 0.50788 was calculated -> https://www.quantstart.com/articles/basics-of-statistical-mean-reversion-testing
In your script c is the equivalent to the Hurst Exponent being calculated in above link? Or are the two methods not comparable?
Hello! Just working with your code on a time series analysis, to compute the Hurst exponent of a equity, e.g. Google.
Here is the code:
import matplotlib.pyplot as plt
from hurst import compute_Hc
from datetime import datetime
import pandas_datareader as web
series = web.DataReader("GOOG", "yahoo", datetime(2000,1,1), datetime(2013,1,1))
H, c, data = compute_Hc(series['Adj Close'], kind='price', simplified=True)
Output: H 0.82083 C 0.5268
Following this resource for the Google stock a Hurst of 0.50788 was calculated -> https://www.quantstart.com/articles/basics-of-statistical-mean-reversion-testing
In your script c is the equivalent to the Hurst Exponent being calculated in above link? Or are the two methods not comparable?