TimeSeries-HurstExponent

A collection of Python scripts for advanced time series analysis, featuring a refined method for calculating the Hurst exponent. This repository is ideal for researchers and analysts looking to delve into the statistical properties of time series data.

Time Series Analysis Tools

This repository contains Python scripts for analyzing time series data, including the calculation of the Hurst exponent using a refined method.

Description

The scripts provided enable users to perform advanced time series analysis. Key features include:

• refined_hurst_exponent.py: Calculates the Hurst exponent, a measure of the long-term memory of time series data.
• load_dataset.py: Utility script for loading and preprocessing data.

Getting Started

Dependencies

• Python 3.x
• NumPy
• Pandas

Installing

• Clone this repository to your local machine.
• Ensure you have the required dependencies installed.

Executing Program

1. Load your time series data using load_dataset.py.
2. Pass the data to refined_hurst_exponent.py to calculate the Hurst exponent.

import load_dataset
import refined_hurst_exponent

# Load your data
data = load_dataset.load("path_to_your_data.txt")

# Calculate Hurst exponent
hurst = refined_hurst_exponent.calculate(data)