Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics
Leonardo H.S. Fernandes,
José W.L. Silva and
Fernando H.A. de Araujo
Chaos, Solitons & Fractals, 2022, vol. 158, issue C
Abstract:
This paper examines the Brazilian inflation indexes dynamics using the multifractal detrended fluctuations analysis (MF-DFA) and the multifractal detrended cross-correlation analysis (MF-DCCA). We find that the Brazilian inflation indexes (α0 > 0.5) and the pairs of Brazilian Inflation indexes (Δα > 0.5) display a persistent multifractal behaviour, high complexity and skew symmetries. Also, we propose a novel multifractal risk measure (MR) considering the multifractal cross-correlation measure (MRCC). The higher MR and MRCC values indicate the more complex and persistent analyzed phenomenon. In contrast, the lowest MR value indicates less complexity and less persistence. From a Macroeconophysics perspective, our findings clarify that the dynamics of Brazilian inflation indexes and the pairs of Brazilian inflation indexes genuinely have a robust inertial component that makes inflation last for a long time.
Keywords: Macroeconophysics; Brazilian inflation indexes; Multifractality; Cross-correlation; Complexity; Risk measures (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077922002624
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922002624
DOI: 10.1016/j.chaos.2022.112052
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().