In this notebook, we will show how to calculate the Hurst values for different securities.
First, we will import the necessary libraries and then, we will read the csv file with the different security prices using the 'read_csv' method of pandas.
We create functions get_hurst and hurst_plot which calculate and plot the Hurst exponent of all securities. We will be using Hurst value of 0.65 as a threshold to filter the securities. We will consider the securities having Hurst value greater or equal to 0.65 as trending securities.
Hurst exponent of all the commodities except Platinum is higher than our predefined threshold that is 0.65. Crude oil has the maximum Hurst value among all commodities.
Hurst exponent of all stock indices are greater than 0.65, NASDAQ being the highest among them.
All currency pairs have Hurst exponent less than 0.65. Therefore, we will not consider any currency pairs in the time series momentum strategy.
Hurst exponent of all the stock indices are greater than 0.65, SHY being the highest among them.
We know that Hurst exponent greater than 0.5 exhibits trending behaviour. But to find a strong trend in a time series, we set the threshold of 0.65. We will consider only these securities having Hurst exponent greater than 0.65 for momentum strategy.