English

Authors

  • Monique Rafaella Anunciação de Oliveira Federal University of Ouro Preto image/svg+xml
  • Português Português
  • Português Português

DOI:

https://doi.org/10.63801/rmat.v1i1.8528

Keywords:

English

Abstract

In this paper, we present a model based on linearly coupled dissipative harmonic oscillators to characterize asset price dynamics, whose fundamental elements are restoring forces, inertia, and damping. The dynamic variables of the physical system are replaced with logarithmic differences between asset prices and reference prices calculated via moving averages. The model is applied to stocks comprising the Brazilian index Ibovespa. The estimated damping coefficients and spring constants suggest attractive and repulsive forces in the market, with a tendency towards regression to the mean and damped joint market movements. The distributions of these parameters indicate significant variations in the degree of interconnection among the stocks, offering valuable insights for asset selection in hedging strategies. Quantities analogous to kinetic and potential energies display power-law-tailed distributions and multifractal behavior, and their dynamics reveal signs of events that have impacted both domestic and international markets.

References

[1] Ford, G.W., Kac, M., Mazur, P.: Statistical Mechanics of Assemblies of Coupled Oscillators. Journal of Mathematical Physics 6, 504–515 (1965) [2] Caldeira, A.O., Leggett, A.J.: Quantum Tunnelling in a Dissipative System. Annals of Physics 149, 374–456 (1983) [3] Bosco de Magalh˜aes, A.R., Mokarzel, S.G., Nemes, M.C., Terra Cunha, M.O.: Decay Rate and Decoherence Control in Coupled Dissipative Cavities. Physica A: Statistical Mechanics and its Applications 341, 234–250 (2004) [4] Strogatz, S.H.: From Kuramoto to Crawford: Exploring the Onset of Synchronization in Populations of Coupled Oscillators. Physica D: Nonlinear Phenomena 143, 1–20 (2000) [5] D¨orfler, F., Bullo, F.: Synchronization in Complex Networks of Phase Oscillators: A Survey. Automatica 50, 1539–1564 (2014) [6] Agarwal, G.S.: In: Hohler, G. (ed.) Quantum Statistical Theories of Spontaneous Emission and their Relation to Other Approaches. Springer Tracts in Modern Physics, vol. 70. Springer, Berlin (1974) [7] Lidar, D.A., Birgitta Whaley, K.: In: Benatti, F., Floreanini, R. (eds.) Decoherence-Free Subspaces and Subsystems. Lecture Notes in Physics, vol. 622, pp. 83–120. Springer, Berlin (2003) [8] Bosco de Magalh˜aes, A.R.: Searching for Robust Quantum Memories in Many Coupled Oscillators. Physics Letters A 375, 4120–4129 (2011) [9] Frisch, R.: Propagation Problems and Impulse Problems in Dynamic Economics. Economic Essays in Honor of Gustav Cassel, pp. 171–205. George Allen & Unwin, London (1933) [10] Takayasu, M., Mizuno, T., Takayasu, H.: Potential Force Observed in Market Dynamics. Physica A: Statistical Mechanics and its Applications 370, 91–97 (2006) [11] Ataullah, A., Tippett, M.: Equity Prices as a Simple Harmonic Oscillator with Noise. Physica A: Statistical Mechanics and its Applications 382, 557–564 (2007) [12] Ye, C., Huang, J.P.: Non-Classical Oscillator Model for Persistent Fluctuations in Stock Markets. Physica A: Statistical Mechanics and its Applications 387, 1255–1263 (2008) [13] Nastasiuk, V.A.: Fisher Information and Quantum Potential Well Model for Finance. Physics Letters A 379, 1998–2000 (2015) [14] Kulesza, S., Belej, M.: Local Real Estate Markets in Poland as a Network of Damped Harmonic Oscillators. Acta Physica Polonica A 127(3-A), 99–102 (2015) [15] Meng, X., Zhang, J., Xu, J., Guo, H.: Quantum Spatial-Periodic Harmonic Model for Daily Price-Limited Stock Markets. Physica A: Statistical Mechanics and its Applications 438, 154–160 (2015) [16] Meng, X., Zhang, J., Guo, H.: Quantum Brownian Motion Model for the Stock Market. Physica A: Statistical Mechanics and its Applications 452, 281–288 (2016) [17] Xavier, P.O.C., Atman, A.P.F., Bosco de Magalh˜aes, A.R.: Equation-Based Model for the Stock Market. Physical Review E 96, 032305 (2017) [18] Ahn, K., Choi, M.Y., Dai, B., Sohn, S., Yang, B.: Modeling Stock Return Distributions with a Quantum Harmonic Oscillator. Europhysics Letters 120(3), 38003 (2017) [19] Orrell, D.: A Quantum Model of Supply and Demand. Physica A: Statistical Mechanics and its Applications 539, 122928 (2020) [20] Garcia, M.M., Machado Pereira, A.C., Acebal, J.L., Bosco de Magalh˜aes, A.R.: Forecast Model for Financial Time Series: An Approach Based on Harmonic Oscillators. Physica A: Statistical Mechanics and its Applications 549, 124365 (2020) [21] Enders, W.: Applied Econometric Time Series, 4th edn. Wiley, ??? (2015) [22] Resende, C.C., Pereira, A.C.M., Cardoso, R.T.N., Bosco de Magalh˜aes, A.R.: Investigating Market Efficiency Through a Forecasting Model Based on Differential Equations. Physica A: Statistical Mechanics and its Applications 474, 199–212 (2017) [23] Tsay, R.S.: Analysis of Financial Time Series, 3rd edn. Wiley, ??? (2010) [24] Granger, C.W.J., Newbold, P.: Spurious regressions in econometrics. Journal of Econometrics 2(2), 111–120 (1974) [25] Campbell, J.Y., Lo, A.W., MacKinlay, A.C.: The Econometrics of Financial Markets. Princeton University Press, Princeton, New Jersey (1997) [26] Hamilton, J.D.: Time Series Analysis. Princeton University Presss, Princeton (1994) [27] Sanders, A.: The Subprime Crisis and its Role in the Financial Crisis. Journal of Housing Economics 17, 254–261 (2008) [28] Cucinotta, D., Vanelli, M.: WHO Declares COVID-19 a Pandemic. Acta Biomed. 91, 157–160 (2020) [29] Melo Modenesi, A., Luporini, V., Pimentel, D.: In: Arestis, P., Troncoso Baltar, C., Prates, D.M. (eds.) Asymmetric Exchange Rate Pass-Through: Evidence, Inflation Dynamics and Policy Implications for Brazil (1999–2016), pp. 69–99. Springer, Cham (2017) [30] Avritzer, L.: The Rousseff Impeachment and the Crisis of Democracy in Brazil. Critical Policy Studies 11, 352–357 (2017) [31] Nunes, F., Melo, C.R.: Impeachment, Political Crisis and Democracy in Brazil. Revista de Ciencia Pol´ıtica 37(2), 281–304 (2017) [32] Silvestre, B.S., Monteiro, M.S., Viana, F.L.E., Sousa-Filho, J.M.: Challenges for Sustainable Supply Chain Management: When Stakeholder Collaboration Becomes Conducive to Corruption. Journal of Cleaner Production 194, 766–776 (2018) [33] Mantegna, R.N., Stanley, H.E.: Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge University Press, Cambridge (1999) [34] Lux, T., Marchesi, M.: Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market. Nature (London) 397, 498–500 (1999) [35] Gopikrishnan, P., Plerou, V., Nunes Amaral, L.A., Meyer, M., Stanley, H.E.: Scaling of the distribution of fluctuations of financial market indices. Phys. Rev. E 60, 5305–5316 (1999) [36] Cajueiro, D.O., Tabak, B.M.: The hurst exponent over time: testing the assertion that emerging markets are becoming more efficient. Physica A: Statistical Mechanics and its Applications 336(3), 521–537 (2004) [37] Di Matteo, T., Aste, T., Dacorogna, M.M.: Long-Term Memories of Developed and Emerging Markets: Using the Scaling Analysis to Characterize their Stage of Development. Journal of Banking & Finance 29, 827–851 (2005) [38] Atman, B. A. P. F. Amin Gon¸calves: Influence of the investor’s behavior on the complexity of the stock market. Brazilian Journal of Physics (2012) [39] Kwapie´n, J., Dro˙zd˙z, S.: Physical Approach to Complex Systems. Physics Reports 515, 115–226 (2012) [40] Yang, G., Zhu, C.G., An, K.N., Huang, J.P.: Overall Fluctuations and Fat Tails in an Artificial Financial Market: The Two-Sided Impact of Leveraged Trading. Physics Letters A 379, 1857–1863 (2015) [41] Botta, F., Moat, H.S., Stanley, H.E., Preis, T.: Quantifying Stock Return Distributions in Financial Markets. PLoS ONE 10(9), 0135600 (2015) [42] Buonocore, R.J., Aste, T., Di Matteo, T.: Measuring Multiscaling in Financial Time-Series. Chaos, Solitons & Fractals 88, 38–47 (2016) [43] Bosco de Magalhães, A.R.: Wealth Dynamics in a Market with Information Asymmetries. Physical Review E 107, 014305 (2023) [44] Ducha, F.A., Atman, A.P.F., Bosco de Magalhães, A.R.: Information Flux in Complex Networks: Path to Stylized Facts. Physica A: Statistical Mechanics and its Applications 566, 125638 (2021) [45] Clauset, A., Shalizi, C.R., Newman, M.E.J.: Power-Law Distributions in Empirical Data. SIAM Review 51(4), 661–703 (2009) [46] Hurst, H.E.: Long-term storage capacity of reservoirs. Transactions of the American society of civil engineers 116(1), 770–799 (1951) [47] Peng, C.-K., Buldyrev, S.V., Havlin, S., Simons, M., Stanley, H.E., Goldberger, A.L.: Mosaic organization of dna nucleotides. Phys. Rev. E 49, 1685–1689 (1994) [48] Kantelhardt, J.W., Zschiegner, S.A., Koscielny-Bunde, E., Havlin, S., Bunde, A., Stanley, H.E.: Multifractal detrended fluctuation analysis of nonstationary time series. Physica A: Statistical Mechanics and its Applications 316(1), 87–114 (2002)

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2026-06-01

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