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Cryptocurrency momentum effect: DFA and MF-DFA analysis

Author

Listed:
  • Cheng, Qing
  • Liu, Xinyuan
  • Zhu, Xiaowu

Abstract

Cryptocurrency has experienced the skyrocketing and falling back in 2018. Beyond the hype, the specific price movements of different cryptocurrencies should be investigated in a more careful way. Since the cryptocurrency market is a non-linear complex system which are not suitable analyzed by tradition methods, this paper introduces methods from econophysics. Mono-fractal analysis (detrended fluctuation analysis, DFA) is applied to investigate the price movement. Further, multi-fractal fluctuation detrended analysis (MF-DFA) is used for robustness test. Through analyzing four representative cryptocurrencies, our paper finds a strong momentum effect in BTC and ETH market, and a reversion effect in XRP and EOS when large fluctuation occurs. These findings may provide a reference for trading strategy in alternative asset allocations.

Suggested Citation

  • Cheng, Qing & Liu, Xinyuan & Zhu, Xiaowu, 2019. "Cryptocurrency momentum effect: DFA and MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119304480
    DOI: 10.1016/j.physa.2019.04.083
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    Citations

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    Cited by:

    1. Lahmiri, Salim & Bekiros, Stelios, 2021. "The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    2. Wang, Jian & Huang, Menghao & Zhang, Yudong & Kim, Junseok, 2022. "Modification of multifractal analysis based on multiplicative cascade image," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    3. Wang, Fang & Han, Guosheng, 2023. "Coupling correlation adaptive detrended analysis for multiple nonstationary series," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    4. Qiao, Xingzhi & Zhu, Huiming & Hau, Liya, 2020. "Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    5. Mehdi Zolfaghari & Bahram Sahabi, 2021. "The impact of oil price and exchange rate on momentum strategy profits in stock market: evidence from oil-rich developing countries," Review of Managerial Science, Springer, vol. 15(7), pages 1981-2023, October.
    6. Zitis, Pavlos I. & Contoyiannis, Yiannis & Potirakis, Stelios M., 2022. "Critical dynamics related to a recent Bitcoin crash," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Lahmiri, Salim & Bekiros, Stelios, 2020. "Intelligent forecasting with machine learning trading systems in chaotic intraday Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    8. Naeem, Muhammad Abubakr & Farid, Saqib & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2021. "Comparative efficiency of green and conventional bonds pre- and during COVID-19: An asymmetric multifractal detrended fluctuation analysis," Energy Policy, Elsevier, vol. 153(C).
    9. Shahzad, Syed Jawad Hussain & Bouri, Elie & Kayani, Ghulam Mujtaba & Nasir, Rana Muhammad & Kristoufek, Ladislav, 2020. "Are clean energy stocks efficient? Asymmetric multifractal scaling behaviour," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    10. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Ko, Hee-Un & Yoon, Seong-Min & Kang, Sang Hoon, 2020. "Why cryptocurrency markets are inefficient: The impact of liquidity and volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    11. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.
    12. Pawan Kumar Singh & Alok Kumar Pandey & S. C. Bose, 2023. "A new grey system approach to forecast closing price of Bitcoin, Bionic, Cardano, Dogecoin, Ethereum, XRP Cryptocurrencies," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2429-2446, June.
    13. Lahmiri, Salim & Bekiros, Stelios, 2020. "Big data analytics using multi-fractal wavelet leaders in high-frequency Bitcoin markets," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    14. Maciel, Leandro, 2021. "A new approach to portfolio management in the Brazilian equity market: Does assets efficiency level improve performance?," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 38-56.
    15. Correia, J.P. & de Lima, M.M.F. & Silva, R. & Anselmo, D.H.A.L. & Vasconcelos, M.S. & Viswanathan, G.M., 2023. "Multifractal analysis of coronavirus sequences," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    16. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    17. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    18. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    19. Kerolly Kedma Felix do Nascimento & Fábio Sandro dos Santos & Jader Silva Jale & Silvio Fernando Alves Xavier Júnior & Tiago A. E. Ferreira, 2023. "Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1095-1114, March.
    20. Ha Nguyen & Bin Liu & Nirav Y. Parikh, 2020. "Exploring the short-term momentum effect in the cryptocurrency market," Evolutionary and Institutional Economics Review, Springer, vol. 17(2), pages 425-443, July.
    21. Borgards, Oliver, 2021. "Dynamic time series momentum of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    22. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).

    More about this item

    Keywords

    Cryptocurrency; Momentum effect; DFA; MF-DFA;
    All these keywords.

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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