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MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS

Year 2013, Volume: 5 Issue: 1, 44 - 55, 01.06.2013

Cumhur Taş Gazanfer Ünal

https://izlik.org/JA72PM28PK

Abstract

We make a comparative study of Multifractal Detrended Fluctuation Analysis (MF-DFA) and the Wavelet Transform Modulus Maxima (WTMM) method to detect multifractal character of natural gas daily returns. We give a brief introduction on above methods and compare their effectiveness. The results from this methodoligies show that behaviour of natural gas daily returns were multifractal. The major sources of multifractality are long-range correlations of small and large fluctuations and Fat-tail distributions of the series

Keywords

Natural Gas Multifractal MF-DFA WTMM

References

  • B.B. Manderlbrot,The Fractal Geometry ofNature, FreemanWH,New York, 1982.
  • W.Kantelhardt, S.A.Zschiegner, E.Koscienlny-Bunde, S. Havlin,Multifractal detrended fluctuation analysis of nonstationary time series,Physica A316 (2002) _114.
  • Muzy, J. F., Bacry, E. & Arneodo, A. (1994) The multifractal formalism revisited with wavelets. Int. J. Bifurc. Chaos. 4, 245-302. (1994)
  • Struzik. Z. R. (2000) Determining local singularity strengths and their spectra with the wavelet transform. Fractals 8, 163-179
  • Andrejs Puckovs, Andrejs Matvejevs, Wavelet Transform Modulus Maxima Approach for World Stock Index Multifractal Analysis.University,Information Technology and Management Science. pp76-86. Espen Ihlen (2012),”Introduction to multifractal detrended fluctuation analysis in
  • Matlab”,Frontiers in Physiology K. Matia, Y. Ashkenazy, H.E. Stanley, Multifractal properties of price fluctuations of stock and commodities, Europhysics Letter 61 (2003) 422–428.
  • Mallat, S. G. and Hwang, W. L. (1990). Technical Report #549, Computer
  • Science Department, New York University, unpublished. Muzy, J. F., Bacry, E. and Arneodo, A. (1991). Wavelets and multifractal formalism for singular signals: Application to turbulence data. Physical Review Letters, 67(25), 3515–3518.
  • Yalamova, R. (2003). Wavelet MRA of index patterns around financial market shocks. Ph.D. thesis, Kent State University.

Year 2013, Volume: 5 Issue: 1, 44 - 55, 01.06.2013

Cumhur Taş Gazanfer Ünal

https://izlik.org/JA72PM28PK

Abstract

References

  • B.B. Manderlbrot,The Fractal Geometry ofNature, FreemanWH,New York, 1982.
  • W.Kantelhardt, S.A.Zschiegner, E.Koscienlny-Bunde, S. Havlin,Multifractal detrended fluctuation analysis of nonstationary time series,Physica A316 (2002) _114.
  • Muzy, J. F., Bacry, E. & Arneodo, A. (1994) The multifractal formalism revisited with wavelets. Int. J. Bifurc. Chaos. 4, 245-302. (1994)
  • Struzik. Z. R. (2000) Determining local singularity strengths and their spectra with the wavelet transform. Fractals 8, 163-179
  • Andrejs Puckovs, Andrejs Matvejevs, Wavelet Transform Modulus Maxima Approach for World Stock Index Multifractal Analysis.University,Information Technology and Management Science. pp76-86. Espen Ihlen (2012),”Introduction to multifractal detrended fluctuation analysis in
  • Matlab”,Frontiers in Physiology K. Matia, Y. Ashkenazy, H.E. Stanley, Multifractal properties of price fluctuations of stock and commodities, Europhysics Letter 61 (2003) 422–428.
  • Mallat, S. G. and Hwang, W. L. (1990). Technical Report #549, Computer
  • Science Department, New York University, unpublished. Muzy, J. F., Bacry, E. and Arneodo, A. (1991). Wavelets and multifractal formalism for singular signals: Application to turbulence data. Physical Review Letters, 67(25), 3515–3518.
  • Yalamova, R. (2003). Wavelet MRA of index patterns around financial market shocks. Ph.D. thesis, Kent State University.
There are 9 citations in total.

Details

Other ID JA56SZ47JJ
Authors

Cumhur Taş This is me

Gazanfer Ünal This is me

Publication Date June 1, 2013
IZ https://izlik.org/JA72PM28PK
Published in Issue Year 2013 Volume: 5 Issue: 1

Cite

APA Taş, C., & Ünal, G. (2013). MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS. International Journal of Economics and Finance Studies, 5(1), 44-55. https://izlik.org/JA72PM28PK
AMA 1.Taş C, Ünal G. MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS. IJEFS. 2013;5(1):44-55. https://izlik.org/JA72PM28PK
Chicago Taş, Cumhur, and Gazanfer Ünal. 2013. “MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS”. International Journal of Economics and Finance Studies 5 (1): 44-55. https://izlik.org/JA72PM28PK.
EndNote Taş C, Ünal G (June 1, 2013) MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS. International Journal of Economics and Finance Studies 5 1 44–55.
IEEE [1]C. Taş and G. Ünal, “MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS”, IJEFS, vol. 5, no. 1, pp. 44–55, June 2013, [Online]. Available: https://izlik.org/JA72PM28PK
ISNAD Taş, Cumhur - Ünal, Gazanfer. “MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS”. International Journal of Economics and Finance Studies 5/1 (June 1, 2013): 44-55. https://izlik.org/JA72PM28PK.
JAMA 1.Taş C, Ünal G. MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS. IJEFS. 2013;5:44–55.
MLA Taş, Cumhur, and Gazanfer Ünal. “MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS”. International Journal of Economics and Finance Studies, vol. 5, no. 1, June 2013, pp. 44-55, https://izlik.org/JA72PM28PK.
Vancouver 1.Cumhur Taş, Gazanfer Ünal. MULTIFRACTAL BEHAVIOUR IN NATURAL GAS PRICES BY USING MF-DFA AND WTMM METHODS. IJEFS [Internet]. 2013 Jun. 1;5(1):44-55. Available from: https://izlik.org/JA72PM28PK