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Testing Non-Linear Dynamics, Long Memory And Chaotic Behaviour Of Energy Commodities

Author

Listed:
  • Murat GENCER

    (Yeditepe University, Turkey)

  • Gazanfer ÜNAL

    (Yeditepe University, Turkey)

Abstract

This paper contains a set of tests for nonlinearities in energy commodity prices. The tests comprise both standart diagnostic tests for revealing nonlinearities. The latter test procedures make use of models in chaos theory, so-called long-memory models and some asymmetric adjustment models. Empirical tests are carried out with daily data for crude oil, heating oil, gasoline and natural gas time series covering the period 2010-2015. Test result showed that there are strong nonlinearities in the data. The test for chaos, however, is weak or no existing. The evidence on long memory (in terms of rescaled range and fractional differencing) is somewhat stronger although not very compelling.

Suggested Citation

  • Murat GENCER & Gazanfer ÜNAL, 2016. "Testing Non-Linear Dynamics, Long Memory And Chaotic Behaviour Of Energy Commodities," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 7(2), pages 85-97.
    • Handle: RePEc:srs:jtpref:v:7:y:2016:i:2:p:85-97
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    Cited by:

    1. Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
    2. Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
    3. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).

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