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Year 2023, Volume: 5 Issue: 2, 78 - 89, 31.07.2023
https://doi.org/10.51537/chaos.1260049

Abstract

References

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  • Baki, U., 2022b Stability analysis of bitcoin using recurrence quantification analysis. Chaos Theory and Applications 4: 104–110.
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  • Kamphorst, J.-P., D. Ruelle, et al., 1987 Recurrence plots of dynamical systems. Europhysics Letters 4: 17.
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  • Schumpeter, J. A., 1976 Ii. capitalism, socialism, and democracy, 1942 .
  • Soloviev, V., O. Serdiuk, S. Semerikov, and A. Kiv, 2020 Recurrence plot-based analysis of financial-economic crashes. CEUR Workshop Proceedings.
  • Soloviev, V. N. and A. Belinskiy, 2019 Complex systems theory and crashes of cryptocurrency market. In Information and Communication Technologies in Education, Research, and Industrial Applications: 14th International Conference, ICTERI 2018, Kyiv, Ukraine, May 14-17, 2018, Revised Selected Papers 14, pp. 276–297, Springer.
  • Wu, Q., M. Wang, and L. Tian, 2020 The market-linkage of the volatility spillover between traditional energy price and carbon price on the realization of carbon value of emission reduction behavior. Journal of Cleaner Production 245: 118682.
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Investigation of the Relationship Between Chaos Data and €/$ Exchange Rate Index Data with RQA Method

Year 2023, Volume: 5 Issue: 2, 78 - 89, 31.07.2023
https://doi.org/10.51537/chaos.1260049

Abstract

A time series data contains a large amount of information in itself. Chaos data and volatility data which calculated by any time series are also derivative information included in the same time series. According to these assumptions, it is very important to question the ability of chaos and volatility information to affect each other, and which information affects and which information is affected. It is very important to determine the causes of volatility, which is an important result indicator for the finance literature, and especially with this study, it was tried to determine whether the chaos data is in a causal relationship with volatility. If some of the chaos data can be identified as the cause of volatility, the detected chaos data can be used in other research as a leading indicator of volatility. The data set used in the study is the daily euro/dollar exchange rate index between 01.01.2005 and 10.11.2022. In the study, time series of chaos data were created with Windowed RQA method and Hatemi-J asymmetric causality analysis research was carried out between these time series and euro/dollar exchange rate index volatility. The findings of the study conclude that the chaos data LnRR, LnEntr and LnLAM could be used as leading indicators of the euro/dollar exchange rate index volatility.

References

  • Baki, U., 2022a Nonlinear chaotic analysis of usd/try and eur/try exchange rates. Eski¸sehir Osmangazi Üniversitesi ˙Iktisadi ve ˙Idari Bilimler Dergisi 17: 410–432.
  • Baki, U., 2022b Stability analysis of bitcoin using recurrence quantification analysis. Chaos Theory and Applications 4: 104–110.
  • Bastos, J. A. and J. Caiado, 2011 Recurrence quantification analysis of global stock markets. Physica A: Statistical Mechanics and its Applications 390: 1315–1325.
  • Belaire-Franch, J., 2004 Testing for non-linearity in an artificial financial market: a recurrence quantification approach. Journal of Economic Behavior & Organization 54: 483–494.
  • Celik, M. Y. and K. E. Afsar, 2010 Finansal zaman serilerinde yineleme haritaları analizi: ˙Imkb Örne˘ gi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi .
  • Coco, M. I. and R. Dale, 2014 Cross-recurrence quantification analysis of categorical and continuous time series: an r package. Frontiers in psychology 5: 510.
  • Coco, M. I., D. Mønster, G. Leonardi, R. Dale, and S. Wallot, 2020 Unidimensional and multidimensional methods for recurrence quantification analysis with crqa. arXiv preprint arXiv:2006.01954 .
  • Engle, R. F. and C. W. Granger, 1987 Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society pp. 251–276.
  • Facchini, A., A. Rubino, G. Caldarelli, and G. Di Liddo, 2019 Changes to gate closure and its impact on wholesale electricity prices: The case of the uk. Energy Policy 125: 110–121.
  • Hatemi-j, A., 2012 Asymmetric causality tests with an application. Empirical economics 43: 447–456.
  • Kamphorst, J.-P., D. Ruelle, et al., 1987 Recurrence plots of dynamical systems. Europhysics Letters 4: 17.
  • Karagianni, S. and C. Kyrtsou, 2011 Analysing the dynamics between us inflation and dow jones index using non-linear methods. Studies in Nonlinear Dynamics & Econometrics 15.
  • Marwan, N. and J. Kurths, 2002 Nonlinear analysis of bivariate data with cross recurrence plots. Physics Letters A 302: 299–307.
  • Mert, M. and A. E. Ça˘ glar, 2019 Eviews ve gauss uygulamalı zaman serileri analizi. Ankara: Detay Yayıncılık pp. 183–213.
  • Niu, H. and L. Zhang, 2017 Nonlinear multiscale entropy and recurrence quantification analysis of foreign exchange markets efficiency. Entropy 20: 17.
  • Orlando, G. and G. Zimatore, 2018 Recurrence quantification analysis of business cycles. Chaos, Solitons & Fractals 110: 82–94.
  • Piskun, O. and S. Piskun, 2011 Recurrence quantification analysis of financial market crashes and crises. arXiv preprint arXiv:1107.5420 .
  • Sasikumar, A. and B. Kamaiah, 2014 A complex dynamical analysis of the indian stock market. Economics Research International 2014.
  • Schumpeter, J. A., 1976 Ii. capitalism, socialism, and democracy, 1942 .
  • Soloviev, V., O. Serdiuk, S. Semerikov, and A. Kiv, 2020 Recurrence plot-based analysis of financial-economic crashes. CEUR Workshop Proceedings.
  • Soloviev, V. N. and A. Belinskiy, 2019 Complex systems theory and crashes of cryptocurrency market. In Information and Communication Technologies in Education, Research, and Industrial Applications: 14th International Conference, ICTERI 2018, Kyiv, Ukraine, May 14-17, 2018, Revised Selected Papers 14, pp. 276–297, Springer.
  • Wu, Q., M. Wang, and L. Tian, 2020 The market-linkage of the volatility spillover between traditional energy price and carbon price on the realization of carbon value of emission reduction behavior. Journal of Cleaner Production 245: 118682.
  • Zbilut, J. P., N. Thomasson, and C. L. Webber, 2002 Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals. Medical engineering & physics 24: 53–60.
  • Zbilut, J. P. and C. L. Webber Jr, 2006 Recurrence quantification analysis. Wiley encyclopedia of biomedical engineering .
There are 24 citations in total.

Details

Primary Language English
Subjects Finance
Journal Section Research Articles
Authors

Hüseyin Serdar Yalçınkaya 0000-0002-5064-5144

Nizamettin Başaran 0000-0002-0459-1819

Early Pub Date May 22, 2023
Publication Date July 31, 2023
Published in Issue Year 2023 Volume: 5 Issue: 2

Cite

APA Yalçınkaya, H. S., & Başaran, N. (2023). Investigation of the Relationship Between Chaos Data and €/$ Exchange Rate Index Data with RQA Method. Chaos Theory and Applications, 5(2), 78-89. https://doi.org/10.51537/chaos.1260049

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

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