Advanced analytical, numerical and analysis methods of applied fluid mechanics and complex systems

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Advanced analytical, numerical and analysis methods of applied fluid mechanics and complex systems (en)
Напредне аналитичке, нумеричке и методе анализе примењене механике флуида и комплексних система (sr)
Napredne analitičke, numeričke i metode analize primenjene mehanike fluida i kompleksnih sistema (sr_RS)
Authors

Publications

Analysis of cyclical behavior in time series of stock market returns

Stratimirović, Đorđe; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana

(Elsevier Science Bv, Amsterdam, 2018)

TY  - JOUR
AU  - Stratimirović, Đorđe
AU  - Sarvan, Darko
AU  - Miljković, Vladimir
AU  - Blesić, Suzana
PY  - 2018
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2329
AB  - In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time- dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differ-entiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.
PB  - Elsevier Science Bv, Amsterdam
T2  - Communications in Nonlinear Science & Numerical Simulation
T1  - Analysis of cyclical behavior in time series of stock market returns
VL  - 54
SP  - 21
EP  - 33
DO  - 10.1016/j.cnsns.2017.05.009
ER  - 
@article{
author = "Stratimirović, Đorđe and Sarvan, Darko and Miljković, Vladimir and Blesić, Suzana",
year = "2018",
abstract = "In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time- dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differ-entiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.",
publisher = "Elsevier Science Bv, Amsterdam",
journal = "Communications in Nonlinear Science & Numerical Simulation",
title = "Analysis of cyclical behavior in time series of stock market returns",
volume = "54",
pages = "21-33",
doi = "10.1016/j.cnsns.2017.05.009"
}
Stratimirović, Đ., Sarvan, D., Miljković, V.,& Blesić, S.. (2018). Analysis of cyclical behavior in time series of stock market returns. in Communications in Nonlinear Science & Numerical Simulation
Elsevier Science Bv, Amsterdam., 54, 21-33.
https://doi.org/10.1016/j.cnsns.2017.05.009
Stratimirović Đ, Sarvan D, Miljković V, Blesić S. Analysis of cyclical behavior in time series of stock market returns. in Communications in Nonlinear Science & Numerical Simulation. 2018;54:21-33.
doi:10.1016/j.cnsns.2017.05.009 .
Stratimirović, Đorđe, Sarvan, Darko, Miljković, Vladimir, Blesić, Suzana, "Analysis of cyclical behavior in time series of stock market returns" in Communications in Nonlinear Science & Numerical Simulation, 54 (2018):21-33,
https://doi.org/10.1016/j.cnsns.2017.05.009 . .
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Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number

Sarvan, Darko; Stratimirović, Đorđe; Blesić, Suzana; Đurđević, Vladimir; Miljković, Vladimir; Ajtić, Jelena

(Elsevier, Amsterdam, 2017)

TY  - JOUR
AU  - Sarvan, Darko
AU  - Stratimirović, Đorđe
AU  - Blesić, Suzana
AU  - Đurđević, Vladimir
AU  - Miljković, Vladimir
AU  - Ajtić, Jelena
PY  - 2017
UR  - https://smile.stomf.bg.ac.rs/handle/123456789/2198
AB  - The dynamics of the beryllium-7 specific activity in surface air over 1987-2011 is analyzed using wavelet transform (WT) analysis and time -dependent detrended moving average (tdDMA) method, WT analysis gives four periodicities in the beryllium-7 specific activity: one month, three months, one year, and three years. These intervals are further used in tdDMA to calculate local autocorrelation exponents for precipitation, tropopause height and teleconnection indices. Our results show that these parameters share common periods with the beryllium-7 surface concentration. tdDMA method indicates that on the characteristic intervals of one year and shorter, the beryllium-7 specific activity is strongly autocorrelated. On the three-year interval, the beryllium-7 specific activity shows periods of anticorrelat ion, implying slow changes in its dynamics that become evident only over a prolonged period of time. A comparison of the Hurst exponents of all the variables on the one- and three-year intervals suggest some similarities in their dynamics. Overall, a good agreement in the behavior of the teleconnection indices and specific activity of beryllium-7 in surface air is noted.
PB  - Elsevier, Amsterdam
T2  - Physica A-Statistical Mechanics & its Applications
T1  - Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number
VL  - 469
SP  - 813
EP  - 823
DO  - 10.1016/j.physa.2016.11.040
ER  - 
@article{
author = "Sarvan, Darko and Stratimirović, Đorđe and Blesić, Suzana and Đurđević, Vladimir and Miljković, Vladimir and Ajtić, Jelena",
year = "2017",
abstract = "The dynamics of the beryllium-7 specific activity in surface air over 1987-2011 is analyzed using wavelet transform (WT) analysis and time -dependent detrended moving average (tdDMA) method, WT analysis gives four periodicities in the beryllium-7 specific activity: one month, three months, one year, and three years. These intervals are further used in tdDMA to calculate local autocorrelation exponents for precipitation, tropopause height and teleconnection indices. Our results show that these parameters share common periods with the beryllium-7 surface concentration. tdDMA method indicates that on the characteristic intervals of one year and shorter, the beryllium-7 specific activity is strongly autocorrelated. On the three-year interval, the beryllium-7 specific activity shows periods of anticorrelat ion, implying slow changes in its dynamics that become evident only over a prolonged period of time. A comparison of the Hurst exponents of all the variables on the one- and three-year intervals suggest some similarities in their dynamics. Overall, a good agreement in the behavior of the teleconnection indices and specific activity of beryllium-7 in surface air is noted.",
publisher = "Elsevier, Amsterdam",
journal = "Physica A-Statistical Mechanics & its Applications",
title = "Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number",
volume = "469",
pages = "813-823",
doi = "10.1016/j.physa.2016.11.040"
}
Sarvan, D., Stratimirović, Đ., Blesić, S., Đurđević, V., Miljković, V.,& Ajtić, J.. (2017). Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number. in Physica A-Statistical Mechanics & its Applications
Elsevier, Amsterdam., 469, 813-823.
https://doi.org/10.1016/j.physa.2016.11.040
Sarvan D, Stratimirović Đ, Blesić S, Đurđević V, Miljković V, Ajtić J. Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number. in Physica A-Statistical Mechanics & its Applications. 2017;469:813-823.
doi:10.1016/j.physa.2016.11.040 .
Sarvan, Darko, Stratimirović, Đorđe, Blesić, Suzana, Đurđević, Vladimir, Miljković, Vladimir, Ajtić, Jelena, "Dynamics of beryllium-7 specific activity in relation to meteorological variables, tropopause height, teleconnection indices and sunspot number" in Physica A-Statistical Mechanics & its Applications, 469 (2017):813-823,
https://doi.org/10.1016/j.physa.2016.11.040 . .
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