Mixed-correlated ARFIMA processes for power-law cross-correlations

By Ladislav Kristoufek. 2013

48 citations recorded by the source corpus.

We introduce a general framework of the Mixed-correlated ARFIMA (MC-ARFIMA) processes which allows for various specifications of univariate and bivariate long-term memory. Apart from a standard case when Hxy=12(Hx+Hy), MC-ARFIMA also allows for processes with Hxy<12(Hx+Hy) but also for long-range correlated processes which are either short-range cross-correlated or simply correlated. The major contribution of MC-ARFIMA lies in the fact that the processes have well-defined asymptotic properties for Hx, Hy and Hxy, which are derived in the paper, so that the processes can be used in simulation studies comparing various estimators of the bivariate Hurst exponent Hxy. Moreover, the framework allows for modeling of processes which are found to have Hxy<12(Hx+Hy).

Subfields: Condensed Matter Physics, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/49e8a6012d2f696ecc294956727f9d7ea430ad19

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Condensed Matter Physics

1. Ladislav Kristoufek

In Economics and Econometrics

1. Ladislav Kristoufek
2. Elie Bouri
3. Eduard Baumöhl
4. Ayoub Ammy-Driss
5. Matthieu Garcin
6. Miloslav S. Vosvrda
7. Rangan Gupta
8. David Roubaud

In Finance

1. Ladislav Kristoufek
2. Ayoub Ammy-Driss
3. Matthieu Garcin
4. Miloslav S. Vosvrda
5. Eduard Baumöhl

Citations in the corpus

• Measuring correlations between non-stationary series with DCCA coefficient (2013, background): “Several processes mimicking the power-law cross-correlations have been proposed as well [25,23,26].”