Measuring correlations between non-stationary series with DCCA coefficient

By Ladislav Kristoufek. 2013

200 citations recorded by the source corpus.

In this short report, we investigate the ability of the DCCA coefficient to measure correlation level between non-stationary series. Based on a wide Monte Carlo simulation study, we show that the DCCA coefficient can estimate the correlation coefficient accurately regardless the strength of non-stationarity (measured by the fractional differencing parameter d). For a comparison, we also report the results for the standard Pearson correlation coefficient. The DCCA coefficient dominates the Pearson coefficient for non-stationary series.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f944b9bea481b6d85f3866c966e996a012d85940

How researchers see this paper

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

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

In Management Science and Operations Research

1. Ladislav Kristoufek
2. Elie Bouri
3. Rangan Gupta
4. David Roubaud
5. Saralees Nadarajah
6. Jeffrey Chu

Citations in the corpus

• Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series (2013, methodology): “Email address: kristouf@utia.cas.cz (Ladislav Kristoufek) Preprint submitted to Physica A November 5, 2013 ar X iv :1 31 1.”