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Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics

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  • Fernandes, Leonardo H.S.
  • Silva, José W.L.
  • de Araujo, Fernando H.A.

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.

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  • Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A., 2022. "Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922002624
    DOI: 10.1016/j.chaos.2022.112052
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    as
    1. Giorgio E. Primiceri, 2006. "Why Inflation Rose and Fell: Policy-Makers' Beliefs and U. S. Postwar Stabilization Policy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 867-901.
    2. Ruge-Murcia, Francisco J, 2003. "Inflation Targeting under Asymmetric Preferences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(5), pages 763-785, October.
    3. Fernando H. A. De Araãšjo & Leonardo H. S. Fernandes & Benjamin M. Tabak, 2021. "Effects Of Covid-19 On Chinese Sectoral Indices: A Multifractal Analysis," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(07), pages 1-13, November.
    4. Kevin B. Grier & Ólan T. Henry & Nilss Olekalns & Kalvinder Shields, 2004. "The asymmetric effects of uncertainty on inflation and output growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 551-565.
    5. Podobnik, Boris & Christopher Crawford, G. & Lichtenstein, Benyamin & Lipic, Tomislav & Wild, Dorian & Zhang, Xin & Stanley, H. Eugene, 2020. "The new wealth of nations: How STEM fields generate the prosperity and inequality of individuals, companies, and countries," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    6. Christopher J. Erceg & Michael D. Bordo & Charles L. Evans, 2000. "Money, Sticky Wages, and the Great Depression," American Economic Review, American Economic Association, vol. 90(5), pages 1447-1463, December.
    7. Xu, Shaofeng, 2017. "Volatility risk and economic welfare," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 17-33.
    8. Hommes, Cars & Lustenhouwer, Joep, 2019. "Inflation targeting and liquidity traps under endogenous credibility," Journal of Monetary Economics, Elsevier, vol. 107(C), pages 48-62.
    9. Aslam, Faheem & Zil-e-huma, & Bibi, Rashida & Ferreira, Paulo, 2022. "Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis," Resources Policy, Elsevier, vol. 75(C).
    10. Silva, Petrônio C.L. & Batista, Paulo V.C. & Lima, Hélder S. & Alves, Marcos A. & Guimarães, Frederico G. & Silva, Rodrigo C.P., 2020. "COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    11. Sarker, Alivia & Mali, Provash, 2021. "Detrended multifractal characterization of Indian rainfall records," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    12. Gintis, Herbert & Bowles, Samuel, 1982. "The Welfare State and Long-Term Economic Growth: Marxian, Neoclassical, and Keynesian Approaches," American Economic Review, American Economic Association, vol. 72(2), pages 341-345, May.
    13. Norman V. Loayza & Romain Rancière & Luis Servén & Jaume Ventura, 2007. "Macroeconomic Volatility and Welfare in Developing Countries: An Introduction," The World Bank Economic Review, World Bank, vol. 21(3), pages 343-357, October.
    14. Gómez-Gómez, Javier & Carmona-Cabezas, Rafael & Ariza-Villaverde, Ana B. & Gutiérrez de Ravé, Eduardo & Jiménez-Hornero, Francisco José, 2021. "Multifractal detrended fluctuation analysis of temperature in Spain (1960–2019)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    15. Ye, Cheng & Qiu, Yanjun & Lu, Guohao & Hou, Yawen, 2018. "Quantitative strategy for the Chinese commodity futures market based on a dynamic weighted money flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1009-1018.
    16. A. Chakraborti & I. Muni-Toke & M. Patriarca & F. Abergel, 2011. "Econophysics Review : II. Agent-based models," Post-Print hal-03332946, HAL.
    17. Farhang Rahmani & Mohammad Hadi Fattahi, 2021. "A multifractal cross-correlation investigation into sensitivity and dependence of meteorological and hydrological droughts on precipitation and temperature," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(3), pages 2197-2219, December.
    18. Wang, Chao & Zhang, Xinyi & Ghadimi, Pezhman & Liu, Qian & Lim, Ming K. & Stanley, H. Eugene, 2019. "The impact of regional financial development on economic growth in Beijing–Tianjin–Hebei region: A spatial econometric analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 635-648.
    19. Lahmiri, Salim, 2018. "Generalized Hurst exponent estimates differentiate EEG signals of healthy and epileptic patients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 378-385.
    20. Benmelech, Efraim & Frydman, Carola & Papanikolaou, Dimitris, 2019. "Financial frictions and employment during the Great Depression," Journal of Financial Economics, Elsevier, vol. 133(3), pages 541-563.
    21. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frédéric Abergel, 2011. "Econophysics review: II. Agent-based models," Post-Print hal-00621059, HAL.
    22. 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.
    23. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    24. Zhao, Zhen-yu & Zhu, Jiang & Xia, Bo, 2016. "Multi-fractal fluctuation features of thermal power coal price in China," Energy, Elsevier, vol. 117(P1), pages 10-18.
    25. Torre, Davide La & Marsiglio, Simone & Mendivil, Franklin & Privileggi, Fabio, 2019. "A stochastic economic growth model with health capital and state-dependent probabilities," Chaos, Solitons & Fractals, Elsevier, vol. 129(C), pages 81-93.
    26. Markus K. Brunnermeier & Yuliy Sannikov, 2014. "A Macroeconomic Model with a Financial Sector," American Economic Review, American Economic Association, vol. 104(2), pages 379-421, February.
    27. Yan, Ruzhen & Yue, Ding & Chen, Xudong & Wu, Xu, 2020. "Non-linear characterization and trend identification of liquidity in China's new OTC stock market based on multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    28. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    29. 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).
    30. Cukierman, Alex & Meltzer, Allan H, 1986. "A Theory of Ambiguity, Credibility, and Inflation under Discretion and Asymmetric Information," Econometrica, Econometric Society, vol. 54(5), pages 1099-1128, September.
    31. Sarra Jribi & Hanen Ben Ismail & Darine Doggui & Hajer Debbabi, 2020. "COVID-19 virus outbreak lockdown: What impacts on household food wastage?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 3939-3955, June.
    32. Victor M. Yakovenko, 2016. "Monetary economics from econophysics perspective," Papers 1608.04832, arXiv.org.
    33. Wang, Jian & Shao, Wei & Kim, Junseok, 2020. "Multifractal detrended cross-correlation analysis between respiratory diseases and haze in South Korea," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    34. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    35. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    36. Rothschild, Emma, 1994. "Adam Smith and the Invisible Hand," American Economic Review, American Economic Association, vol. 84(2), pages 319-322, May.
    37. Charles W. Calomiris & Joseph R. Mason, 2003. "Consequences of Bank Distress During the Great Depression," American Economic Review, American Economic Association, vol. 93(3), pages 937-947, June.
    38. Hensher, David A. & Wei, Edward & Beck, MatthewJ. & Balbontin, Camila, 2021. "The impact of COVID-19 on cost outlays for car and public transport commuting - The case of the Greater Sydney Metropolitan Area after three months of restrictions," Transport Policy, Elsevier, vol. 101(C), pages 71-80.
    39. Tao, Yong, 2021. "Boltzmann-like income distribution in low and middle income classes: Evidence from the United Kingdom," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    40. Hajian, S. & Movahed, M. Sadegh, 2010. "Multifractal Detrended Cross-Correlation Analysis of sunspot numbers and river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4942-4957.
    41. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
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