Research Article
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Time-Varying Fractal Analysis of Exchange Rates

Year 2023, Volume: 5 Issue: 3, 242 - 255, 30.11.2023
https://doi.org/10.51537/chaos.1305009

Abstract

The foreign exchange (forex) market is a dynamic and complex financial arena where the exchange rates of various currency pairs fluctuate continuously. Among these currency pairs, EUR/TRY and USD/TRY hold significant economic relevance due to their roles in international trade and finance. In this study, we analyze the multifractality of hourly EUR/TRY and USD/TRY exchange rate data for the whole period, as well as its time-varying individual and cross correlations, spanning from May 31, 2018, to March 21, 2022. We employ multifractal detrended cross-correlation analysis (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) methodologies. The aim of studying multifractality in exchange rates is to comprehend and model the complex and intricate nature of price movements and dynamics of the EUR/TRY and USD/TRY exchange rates. In the analysis of the whole period, multifractality is detected in individual exchange rates and cross correlations. In the rolling window analysis, we demonstrated how multifractality and cross correlation multifractality change over time. Additionally, contributions of the sources of the multifractality are investigated in a time-varying framework. Multifractal nature of these exchange rates indicate that they exhibit complex and scale-dependent behaviors, which go beyond the traditional linear models. The existence of multifractality in EUR/TRY and USD/TRY exchange rates has significant implications for financial modeling, risk management, and trading strategies. It implies that standard linear models may not capture the full complexity of these markets, necessitating the development of more sophisticated models that account for multifractal properties.

References

  • Ashkenazy, Y., P. C. Ivanov, S. Havlin, C.-K. Peng, A. L. Goldberger, et al., 2001 Magnitude and sign correlations in heartbeat fluctuations. Physical Review Letters 86: 1900.
  • Blesi´c, S., S. Miloševi´c, D. Stratimirovi´c, and M. Ljubisavljevi´c, 1999 Detrended fluctuation analysis of time series of a firing fusimotor neuron. Physica A: Statistical Mechanics and its Applications 268: 275–282.
  • Buldyrev, S., N. Dokholyan, A. Goldberger, S. Havlin, C.-K. Peng, et al., 1998 Analysis of dna sequences using methods of statistical physics. Physica A: Statistical Mechanics and its Applications 249: 430–438.
  • Bunde, A., S. Havlin, J. W. Kantelhardt, T. Penzel, J.-H. Peter, et al., 2000 Correlated and uncorrelated regions in heart-rate fluctuations during sleep. Physical review letters 85: 3736.
  • Caraiani, P. and E. Haven, 2015 Evidence of multifractality from cee exchange rates against euro. Physica A: Statistical Mechanics and its Applications 419: 395–407.
  • Chen, S.-P. and L.-Y. He, 2010 Multifractal spectrum analysis of nonlinear dynamical mechanisms in china’s agricultural futures markets. Physica A: Statistical Mechanics and its Applications 389: 1434–1444.
  • Dashtian, H., G. R. Jafari, M. Sahimi, and M. Masihi, 2011 Scaling, multifractality, and long-range correlations in well log data of large-scale porous media. Physica A: Statistical Mechanics and its Applications 390: 2096–2111.
  • Fama, E. F., 1965 The behavior of stock-market prices. The journal of Business 38: 34–105.
  • Gneiting, T., H. Ševˇcíková, and D. B. Percival, 2012 Estimators of fractal dimension: Assessing the roughness of time series and spatial data. Statistical Science pp. 247–277.
  • Gülba¸s, E. and Ü. Gazanfer, 2013 Multifractal analysis of the dynamics of turkish exchange rate. International Journal of Economics and Finance Studies 5: 96–107.
  • Han, C., Y.Wang, and Y. Ning, 2019 Comparative analysis of the multifractality and efficiency of exchange markets: Evidence from exchange rates dynamics of major world currencies. Physica A: Statistical Mechanics and its Applications 535: 122365.
  • He, L.-Y. and S.-P. Chen, 2010a Are crude oil markets multifractal? evidence from mf-dfa and mf-ssa perspectives. Physica A: Statistical Mechanics and its Applications 389: 3218–3229.
  • He, L.-Y. and S.-P. Chen, 2010b Are developed and emerging agricultural futures markets multifractal? a comparative perspective. Physica A: Statistical Mechanics and its Applications 389: 3828– 3836.
  • Hu, K., P. C. Ivanov, Z. Chen, P. Carpena, and H. E. Stanley, 2001 Effect of trends on detrended fluctuation analysis. Physical Review E 64: 011114.
  • Hurst, H. E., 1951 Long-term storage capacity of reservoirs. Transactions of the American society of civil engineers 116: 770–799.
  • Hurst, H. E., 1957 A suggested statistical model of some time series which occur in nature. Nature 180: 494–494.
  • Jafari, G. R., P. Pedram, and L. Hedayatifar, 2007 Long-range correlation and multifractality in bach’s inventions pitches. Journal of Statistical Mechanics: Theory and Experiment 2007: P04012.
  • Kantelhardt, J. W., E. Koscielny-Bunde, H. H. Rego, S. Havlin, and A. Bunde, 2001 Detecting long-range correlations with detrended fluctuation analysis. Physica A: Statistical Mechanics and its Applications 295: 441–454.
  • Kantelhardt, J. W., D. Rybski, S. A. Zschiegner, P. Braun, E. Koscielny-Bunde, et al., 2003 Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods. Physica A: Statistical Mechanics and its Applications 330: 240–245.
  • Kantelhardt, J. W., S. A. Zschiegner, E. Koscielny-Bunde, S. Havlin, A. Bunde, et al., 2002 Multifractal detrended fluctuation analysis of nonstationary time series. Physica A: Statistical Mechanics and its Applications 316: 87–114.
  • Li, J., X. Lu, and Y. Zhou, 2016 Cross-correlations between crude oil and exchange markets for selected oil rich economies. Physica A: Statistical Mechanics and its Applications 453: 131–143.
  • Lim, K.-P. and R. Brooks, 2011 The evolution of stock market efficiency over time: A survey of the empirical literature. Journal of economic surveys 25: 69–108.
  • Liu, Y., P. Gopikrishnan, H. E. Stanley, et al., 1999 Statistical properties of the volatility of price fluctuations. Physical review e 60: 1390.
  • Lu, X., J. Li, Y. Zhou, and Y. Qian, 2017 Cross-correlations between rmb exchange rate and international commodity markets. Physica A: Statistical Mechanics and its Applications 486: 168–182.
  • Ma, F., Y.Wei, and D. Huang, 2013a Multifractal detrended crosscorrelation analysis between the chinese stock market and surrounding stock markets. Physica A: Statistical Mechanics and its Applications 392: 1659–1670.
  • Ma, F., Y. Wei, D. Huang, and L. Zhao, 2013b Cross-correlations between west texas intermediate crude oil and the stock markets of the bric. Physica A: Statistical Mechanics and its Applications 392: 5356–5368.
  • Ma, F., Q. Zhang, C. Peng, and Y. Wei, 2014 Multifractal detrended cross-correlation analysis of the oil-dependent economies: Evidence from the west texas intermediate crude oil and the gcc stock markets. Physica A: Statistical Mechanics and its Applications 410: 154–166.
  • Mandelbrot, B. B., 1982 The fractal geometry of nature, volume 1. WH freeman New York.
  • Matia, K., Y. Ashkenazy, and H. E. Stanley, 2003 Multifractal properties of price fluctuations of stocks and commodities. Europhysics letters 61: 422.
  • Movahed, M. S., G. Jafari, F. Ghasemi, S. Rahvar, and M. R. R. Tabar, 2006 Multifractal detrended fluctuation analysis of sunspot time series. Journal of Statistical Mechanics: Theory and Experiment 2006: P02003.
  • Peng, C.-K., S. V. Buldyrev, S. Havlin, M. Simons, H. E. Stanley, et al., 1994 Mosaic organization of dna nucleotides. Physical review e 49: 1685.
  • Peters, E. E., 1994 Fractal market analysis: applying chaos theory to investment and economics, volume 24. John Wiley & Sons.
  • Schmitt, F., D. Schertzer, and S. Lovejoy, 1999 Multifractal analysis of foreign exchange data. Applied stochastic models and data analysis 15: 29–53.
  • Scott, A. J. and M. Knott, 1974 A cluster analysis method for grouping means in the analysis of variance. Biometrics pp. 507–512.
  • Sen, A. and M. S. Srivastava, 1975 On tests for detecting change in mean. The Annals of statistics pp. 98–108.
  • Stoši´c, D., D. Stoši´c, T. Stoši´c, and H. E. Stanley, 2015 Multifractal analysis of managed and independent float exchange rates. Physica A: Statistical Mechanics and its Applications 428: 13–18.
  • Talkner, P. and R. O.Weber, 2000 Power spectrum and detrended fluctuation analysis: Application to daily temperatures. Physical Review E 62: 150–160.
  • Tanna, H. and K. Pathak, 2014 Multifractality due to long-range correlation in the l-band ionospheric scintillation s 4 index time series. Astrophysics and Space Science 350: 47–56.
  • Telesca, L., V. Lapenna, and M. Macchiato, 2004 Mono-and multifractal investigation of scaling properties in temporal patterns of seismic sequences. Chaos, Solitons & Fractals 19: 1–15.
  • Wang, Y., Y.Wei, and C.Wu, 2011a Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis. Physica A: Statistical Mechanics and its Applications 390: 817–827.
  • Wang, Y., Y. Wei, and C. Wu, 2011b Detrended fluctuation analysis on spot and futures markets of west texas intermediate crude oil. Physica A: Statistical Mechanics and its Applications 390: 864–875.
  • Xie, C., Y. Zhou, G. Wang, and X. Yan, 2017 Analyzing the crosscorrelation between onshore and offshore rmb exchange rates based on multifractal detrended cross-correlation analysis (mfdcca). Fluctuation and Noise Letters 16: 1750004.
  • Yen, G. and C.-f. Lee, 2008 Efficient market hypothesis (emh): past, present and future. Review of Pacific Basin Financial Markets and Policies 11: 305–329.
  • Yue, P., H.-C. Xu,W. Chen, X. Xiong, and W.-X. Zhou, 2017 Linear and nonlinear correlations in the order aggressiveness of chinese stocks. Fractals 25: 1750041.
  • Zhuang, X., Y. Wei, and F. Ma, 2015 Multifractality, efficiency analysis of chinese stock market and its cross-correlation with wti crude oil price. Physica A: Statistical Mechanics and its Applications 430: 101–113.
  • Zhuang, X., Y. Wei, and B. Zhang, 2014 Multifractal detrended cross-correlation analysis of carbon and crude oil markets. Physica A: Statistical Mechanics and its Applications 399: 113–125.
  • Zunino, L., A. Figliola, B. M. Tabak, D. G. Pérez, M. Garavaglia, et al., 2009 Multifractal structure in latin-american market indices. Chaos, Solitons & Fractals 41: 2331–2340.
Year 2023, Volume: 5 Issue: 3, 242 - 255, 30.11.2023
https://doi.org/10.51537/chaos.1305009

Abstract

References

  • Ashkenazy, Y., P. C. Ivanov, S. Havlin, C.-K. Peng, A. L. Goldberger, et al., 2001 Magnitude and sign correlations in heartbeat fluctuations. Physical Review Letters 86: 1900.
  • Blesi´c, S., S. Miloševi´c, D. Stratimirovi´c, and M. Ljubisavljevi´c, 1999 Detrended fluctuation analysis of time series of a firing fusimotor neuron. Physica A: Statistical Mechanics and its Applications 268: 275–282.
  • Buldyrev, S., N. Dokholyan, A. Goldberger, S. Havlin, C.-K. Peng, et al., 1998 Analysis of dna sequences using methods of statistical physics. Physica A: Statistical Mechanics and its Applications 249: 430–438.
  • Bunde, A., S. Havlin, J. W. Kantelhardt, T. Penzel, J.-H. Peter, et al., 2000 Correlated and uncorrelated regions in heart-rate fluctuations during sleep. Physical review letters 85: 3736.
  • Caraiani, P. and E. Haven, 2015 Evidence of multifractality from cee exchange rates against euro. Physica A: Statistical Mechanics and its Applications 419: 395–407.
  • Chen, S.-P. and L.-Y. He, 2010 Multifractal spectrum analysis of nonlinear dynamical mechanisms in china’s agricultural futures markets. Physica A: Statistical Mechanics and its Applications 389: 1434–1444.
  • Dashtian, H., G. R. Jafari, M. Sahimi, and M. Masihi, 2011 Scaling, multifractality, and long-range correlations in well log data of large-scale porous media. Physica A: Statistical Mechanics and its Applications 390: 2096–2111.
  • Fama, E. F., 1965 The behavior of stock-market prices. The journal of Business 38: 34–105.
  • Gneiting, T., H. Ševˇcíková, and D. B. Percival, 2012 Estimators of fractal dimension: Assessing the roughness of time series and spatial data. Statistical Science pp. 247–277.
  • Gülba¸s, E. and Ü. Gazanfer, 2013 Multifractal analysis of the dynamics of turkish exchange rate. International Journal of Economics and Finance Studies 5: 96–107.
  • Han, C., Y.Wang, and Y. Ning, 2019 Comparative analysis of the multifractality and efficiency of exchange markets: Evidence from exchange rates dynamics of major world currencies. Physica A: Statistical Mechanics and its Applications 535: 122365.
  • He, L.-Y. and S.-P. Chen, 2010a Are crude oil markets multifractal? evidence from mf-dfa and mf-ssa perspectives. Physica A: Statistical Mechanics and its Applications 389: 3218–3229.
  • He, L.-Y. and S.-P. Chen, 2010b Are developed and emerging agricultural futures markets multifractal? a comparative perspective. Physica A: Statistical Mechanics and its Applications 389: 3828– 3836.
  • Hu, K., P. C. Ivanov, Z. Chen, P. Carpena, and H. E. Stanley, 2001 Effect of trends on detrended fluctuation analysis. Physical Review E 64: 011114.
  • Hurst, H. E., 1951 Long-term storage capacity of reservoirs. Transactions of the American society of civil engineers 116: 770–799.
  • Hurst, H. E., 1957 A suggested statistical model of some time series which occur in nature. Nature 180: 494–494.
  • Jafari, G. R., P. Pedram, and L. Hedayatifar, 2007 Long-range correlation and multifractality in bach’s inventions pitches. Journal of Statistical Mechanics: Theory and Experiment 2007: P04012.
  • Kantelhardt, J. W., E. Koscielny-Bunde, H. H. Rego, S. Havlin, and A. Bunde, 2001 Detecting long-range correlations with detrended fluctuation analysis. Physica A: Statistical Mechanics and its Applications 295: 441–454.
  • Kantelhardt, J. W., D. Rybski, S. A. Zschiegner, P. Braun, E. Koscielny-Bunde, et al., 2003 Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods. Physica A: Statistical Mechanics and its Applications 330: 240–245.
  • Kantelhardt, J. W., S. A. Zschiegner, E. Koscielny-Bunde, S. Havlin, A. Bunde, et al., 2002 Multifractal detrended fluctuation analysis of nonstationary time series. Physica A: Statistical Mechanics and its Applications 316: 87–114.
  • Li, J., X. Lu, and Y. Zhou, 2016 Cross-correlations between crude oil and exchange markets for selected oil rich economies. Physica A: Statistical Mechanics and its Applications 453: 131–143.
  • Lim, K.-P. and R. Brooks, 2011 The evolution of stock market efficiency over time: A survey of the empirical literature. Journal of economic surveys 25: 69–108.
  • Liu, Y., P. Gopikrishnan, H. E. Stanley, et al., 1999 Statistical properties of the volatility of price fluctuations. Physical review e 60: 1390.
  • Lu, X., J. Li, Y. Zhou, and Y. Qian, 2017 Cross-correlations between rmb exchange rate and international commodity markets. Physica A: Statistical Mechanics and its Applications 486: 168–182.
  • Ma, F., Y.Wei, and D. Huang, 2013a Multifractal detrended crosscorrelation analysis between the chinese stock market and surrounding stock markets. Physica A: Statistical Mechanics and its Applications 392: 1659–1670.
  • Ma, F., Y. Wei, D. Huang, and L. Zhao, 2013b Cross-correlations between west texas intermediate crude oil and the stock markets of the bric. Physica A: Statistical Mechanics and its Applications 392: 5356–5368.
  • Ma, F., Q. Zhang, C. Peng, and Y. Wei, 2014 Multifractal detrended cross-correlation analysis of the oil-dependent economies: Evidence from the west texas intermediate crude oil and the gcc stock markets. Physica A: Statistical Mechanics and its Applications 410: 154–166.
  • Mandelbrot, B. B., 1982 The fractal geometry of nature, volume 1. WH freeman New York.
  • Matia, K., Y. Ashkenazy, and H. E. Stanley, 2003 Multifractal properties of price fluctuations of stocks and commodities. Europhysics letters 61: 422.
  • Movahed, M. S., G. Jafari, F. Ghasemi, S. Rahvar, and M. R. R. Tabar, 2006 Multifractal detrended fluctuation analysis of sunspot time series. Journal of Statistical Mechanics: Theory and Experiment 2006: P02003.
  • Peng, C.-K., S. V. Buldyrev, S. Havlin, M. Simons, H. E. Stanley, et al., 1994 Mosaic organization of dna nucleotides. Physical review e 49: 1685.
  • Peters, E. E., 1994 Fractal market analysis: applying chaos theory to investment and economics, volume 24. John Wiley & Sons.
  • Schmitt, F., D. Schertzer, and S. Lovejoy, 1999 Multifractal analysis of foreign exchange data. Applied stochastic models and data analysis 15: 29–53.
  • Scott, A. J. and M. Knott, 1974 A cluster analysis method for grouping means in the analysis of variance. Biometrics pp. 507–512.
  • Sen, A. and M. S. Srivastava, 1975 On tests for detecting change in mean. The Annals of statistics pp. 98–108.
  • Stoši´c, D., D. Stoši´c, T. Stoši´c, and H. E. Stanley, 2015 Multifractal analysis of managed and independent float exchange rates. Physica A: Statistical Mechanics and its Applications 428: 13–18.
  • Talkner, P. and R. O.Weber, 2000 Power spectrum and detrended fluctuation analysis: Application to daily temperatures. Physical Review E 62: 150–160.
  • Tanna, H. and K. Pathak, 2014 Multifractality due to long-range correlation in the l-band ionospheric scintillation s 4 index time series. Astrophysics and Space Science 350: 47–56.
  • Telesca, L., V. Lapenna, and M. Macchiato, 2004 Mono-and multifractal investigation of scaling properties in temporal patterns of seismic sequences. Chaos, Solitons & Fractals 19: 1–15.
  • Wang, Y., Y.Wei, and C.Wu, 2011a Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis. Physica A: Statistical Mechanics and its Applications 390: 817–827.
  • Wang, Y., Y. Wei, and C. Wu, 2011b Detrended fluctuation analysis on spot and futures markets of west texas intermediate crude oil. Physica A: Statistical Mechanics and its Applications 390: 864–875.
  • Xie, C., Y. Zhou, G. Wang, and X. Yan, 2017 Analyzing the crosscorrelation between onshore and offshore rmb exchange rates based on multifractal detrended cross-correlation analysis (mfdcca). Fluctuation and Noise Letters 16: 1750004.
  • Yen, G. and C.-f. Lee, 2008 Efficient market hypothesis (emh): past, present and future. Review of Pacific Basin Financial Markets and Policies 11: 305–329.
  • Yue, P., H.-C. Xu,W. Chen, X. Xiong, and W.-X. Zhou, 2017 Linear and nonlinear correlations in the order aggressiveness of chinese stocks. Fractals 25: 1750041.
  • Zhuang, X., Y. Wei, and F. Ma, 2015 Multifractality, efficiency analysis of chinese stock market and its cross-correlation with wti crude oil price. Physica A: Statistical Mechanics and its Applications 430: 101–113.
  • Zhuang, X., Y. Wei, and B. Zhang, 2014 Multifractal detrended cross-correlation analysis of carbon and crude oil markets. Physica A: Statistical Mechanics and its Applications 399: 113–125.
  • Zunino, L., A. Figliola, B. M. Tabak, D. G. Pérez, M. Garavaglia, et al., 2009 Multifractal structure in latin-american market indices. Chaos, Solitons & Fractals 41: 2331–2340.
There are 47 citations in total.

Details

Primary Language English
Subjects Finance
Journal Section Research Articles
Authors

Baki Ünal 0000-0001-9154-0931

Publication Date November 30, 2023
Published in Issue Year 2023 Volume: 5 Issue: 3

Cite

APA Ünal, B. (2023). Time-Varying Fractal Analysis of Exchange Rates. Chaos Theory and Applications, 5(3), 242-255. https://doi.org/10.51537/chaos.1305009

Chaos Theory and Applications in Applied Sciences and Engineering: An interdisciplinary journal of nonlinear science 23830 28903   

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