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Multifractal behavior in the dynamics of Brazilian inflation indices

Author

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  • Fernandes, Leonardo H.S.
  • Araújo, Fernando H.A.
  • Silva, Igor E.M.
  • Leite, Urbanno P.S.
  • de Lima, Neílson F.
  • Stosic, Tatijana
  • Ferreira, Tiago A.E.

Abstract

In this paper, we applied the Multifractal Detrended Fluctuations Analysis (MF-DFA) to investigate the components of the observed multifractality in time series of 6 Brazilian inflation indices. We found the generalized Hurst exponent h(q) for each Brazilian inflation indices and quantify their statistical properties, which allowed us to observe separately the small scale contributing (primarily via the negative moments q) and the large scale (via the positive moments q). We also calculated the multifractal spectrum f(α) and used a fourth-degree polynomial regression fit to estimate the complexity parameters that describe the degree of multifractality of the underlying process. We compared the MF-DFA results for the original time series with those for shuffled series. We found that its multifractal nature is due to two factors: broadness of probability density function of the times series and different correlations in small and large scale fluctuations.

Suggested Citation

  • Fernandes, Leonardo H.S. & Araújo, Fernando H.A. & Silva, Igor E.M. & Leite, Urbanno P.S. & de Lima, Neílson F. & Stosic, Tatijana & Ferreira, Tiago A.E., 2020. "Multifractal behavior in the dynamics of Brazilian inflation indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
  • Handle: RePEc:eee:phsmap:v:550:y:2020:i:c:s0378437120300145
    DOI: 10.1016/j.physa.2020.124158
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    as
    1. Peter N. Ireland, 2009. "On the Welfare Cost of Inflation and the Recent Behavior of Money Demand," American Economic Review, American Economic Association, vol. 99(3), pages 1040-1052, June.
    2. Mizuno, T. & Takayasu, M. & Takayasu, H., 2002. "The mechanism of double-exponential growth in hyper-inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 411-419.
    3. Wei-Xing Zhou, 2009. "The components of empirical multifractality in financial returns," Papers 0908.1089, arXiv.org, revised Oct 2009.
    4. Telesca, Luciano & Lapenna, Vincenzo & Macchiato, Maria, 2005. "Multifractal fluctuations in seismic interspike series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 629-640.
    5. Cooley, Thomas F & Hansen, Gary D, 1989. "The Inflation Tax in a Real Business Cycle Model," American Economic Review, American Economic Association, vol. 79(4), pages 733-748, September.
    6. Jovanovic, Boyan & Ueda, Masako, 1998. "Stock-Returns and Inflation in a Principal-Agent Economy," Journal of Economic Theory, Elsevier, vol. 82(1), pages 223-247, September.
    7. Furlani, Luiz Gustavo Cassilatti & Portugal, Marcelo Savino & Laurini, Márcio Poletti, 2010. "Exchange rate movements and monetary policy in Brazil: Econometric and simulation evidence," Economic Modelling, Elsevier, vol. 27(1), pages 284-295, January.
    8. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    9. de Benicio, Rosilda B. & Stošić, Tatijana & de Figueirêdo, P.H. & Stošić, Borko D., 2013. "Multifractal behavior of wild-land and forest fire time series in Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6367-6374.
    10. Hao Meng & Fei Ren & Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei-Xing Zhou & Wei Zhang, 2012. "Effects of long memory in the order submission process on the properties of recurrence intervals of large price fluctuations," Papers 1201.2825, arXiv.org.
    11. Andreza Aparecida Palma & Marcelo Savino Portugal, 2014. "Preferences Of The Central Bank Of Brazil Under The Inflation Targeting Regime: Estimation Using A Dsge Model For A Small Open Economy," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 055, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    12. Casares, Miguel, 2010. "Unemployment as excess supply of labor: Implications for wage and price inflation," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 233-243, March.
    13. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    14. Cinquetti, Carlos A., 2000. "The Real Plan: Stabilization and Destabilization," World Development, Elsevier, vol. 28(1), pages 155-171, January.
    15. Arminio Fraga & Ilan Goldfajn & André Minella, 2004. "Inflation Targeting in Emerging Market Economies," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 365-416, National Bureau of Economic Research, Inc.
    16. Stošić, Dusan & Stošić, Darko & Stošić, Tatijana & Eugene Stanley, H., 2015. "Multifractal properties of price change and volume change of stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 46-51.
    17. Ariel Burstein & Christian Hellwig, 2008. "Welfare Costs of Inflation in a Menu Cost Model," American Economic Review, American Economic Association, vol. 98(2), pages 438-443, May.
    18. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    19. Palma, Andreza Aparecida & Portugal, Marcelo Savino, 2014. "Preferences of the Central Bank of Brazil under the inflation targeting regime: Estimation using a DSGE model for a small open economy," Journal of Policy Modeling, Elsevier, vol. 36(5), pages 824-839.
    20. T. Di Matteo, 2007. "Multi-scaling in finance," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 21-36.
    21. Szybisz, Martín A. & Szybisz, Leszek, 2017. "Extended nonlinear feedback model for describing episodes of high inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 91-108.
    22. Stanley Fischer, 1981. "Relative Shocks, Relative Price Variability, and Inflation," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 12(2), pages 381-442.
    23. Alfredo Saad-Filho & Maria de Lourdes R. Mollo, 2002. "Inflation and stabilization in Brazil: a political economy analysis," Review of Radical Political Economics, Union for Radical Political Economics, vol. 34(2), pages 109-135, June.
    24. Martijn Cremers & Michael Halling & David Weinbaum, 2015. "Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 70(2), pages 577-614, April.
    25. Resende, Marcelo, 2002. "Relative efficiency measurement and prospects for yardstick competition in Brazilian electricity distribution," Energy Policy, Elsevier, vol. 30(8), pages 637-647, June.
    26. Safdari, H. & Hosseiny, A. & Vasheghani Farahani, S. & Jafari, G.R., 2016. "A picture for the coupling of unemployment and inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 744-750.
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