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Long Memory in Clean Energy Exchange Traded Funds

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  • Arife Özdemir Höl

Abstract

This study aims to investigate whether clean energy exchange traded funds (ETFs) exhibit long-term memory properties and whether the efficient market hypothesis is valid for these assets. The results of the model established to test the dual long memory indicate the existence of long memory in both return and volatility of the ICLN, PBD, PBW series, while the long memory feature is found only in the volatility of the other variables. The results reveal that the selected clean energy ETFs do not exhibit weak efficient market characteristics and volatility has a predictable structure. These results mean that by using the past price movements of clean energy ETFs, future price movements can be predicted and thus above-normal returns can be obtained. In addition, it can be said that risks and uncertainties are effective on the price movements of clean energy ETFs. These results are important for portfolio managers, hedgers and individual and institutional investors aiming to direct their investments to the renewable energy market, as well as for policymakers.

Suggested Citation

  • Arife Özdemir Höl, 2024. "Long Memory in Clean Energy Exchange Traded Funds," Politická ekonomie, Prague University of Economics and Business, vol. 2024(3), pages 478-500.
    • Handle: RePEc:prg:jnlpol:v:2024:y:2024:i:3:id:1415:p:478-500
    DOI: 10.18267/j.polek.1415
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    References listed on IDEAS

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    1. Barkoulas, John T. & Baum, Christopher F., 1996. "Long-term dependence in stock returns," Economics Letters, Elsevier, vol. 53(3), pages 253-259, December.
    2. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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