Have a personal or library account? Click to login
The Predictability of High-Frequency Returns in the Cryptocurrency Markets and the Adaptive Market Hypothesis Cover

The Predictability of High-Frequency Returns in the Cryptocurrency Markets and the Adaptive Market Hypothesis

Open Access
|Feb 2025

References

  1. Apopo, N., &amp; Phiri, A. (2021). On the (In)efficiency of Cryptocurrencies: Have They Taken Daily or Weekly Random Walks? <em>Heliyon</em>, 7(4). <a href="https://doi.org/10.1016/j.heliyon.2021.e06685" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.heliyon.2021.e06685</a>
  2. Aslam, F., Memon, B. A., Hunjra, A. I., &amp; Bouri, E. (2023). The Dynamics of Market Efficiency of Major Cryptocurrencies. <em>Global Finance Journal</em>, 58, 100899. <a href="https://doi.org/10.1016/j.gfj.2023.100899" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.gfj.2023.100899</a>
  3. Aslan, A., &amp; Sensoy, A. (2020). Intraday Efficiency-Frequency Nexus in the Cryptocurrency Markets. <em>Finance Research Letters</em>, 35, 101298. <a href="https://doi.org/10.1016/j.frl.2019.09.013" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2019.09.013</a>
  4. Bundi, N., &amp; Wildi, M. (2019). Bitcoin and Market-(In)efficiency: A Systematic Time Series Approach. <em>Digital Finance</em>, 1, 47–65. <a href="https://doi.org/10.1007/s42521-019-00004-z" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1007/s42521-019-00004-z</a>
  5. Campbell, J. Y., Lo, A. W., &amp; MacKinlay, A. C. (1997). <em>The Econometrics of Financial Markets.</em> Princeton: Princeton University Press.
  6. Caporale, G. M., Gil-Alana, L., &amp; Plastun, A. (2018). Persistence in the Cryptocurrency Market. <em>Research in International Business and Finance</em>, 46(C), 141–148. <a href="https://doi.org/10.1016/j.ribaf.2018.01.002" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.ribaf.2018.01.002</a>
  7. Charles, A., Darné, O., &amp; Kim, J. H. (2011). Small Sample Properties of Alternative Tests for Martingale Difference Hypothesis. <em>Economics Letters</em>, 110(2), 151–154. <a href="https://doi.org/10.1016/j.econlet.2010.11.018" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.econlet.2010.11.018</a>
  8. Charles, A., Darné, O., &amp; Kim, J. H. (2012). Exchange-Rate Return Predictability and the Adaptive Markets Hypothesis: Evidence From Major Foreign Exchange Rates. <em>Journal of International Money and Finance</em>, 31(6), 1607–1626. <a href="https://doi.org/10.1016/j.jimonfin.2012.03.003" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.jimonfin.2012.03.003</a>
  9. Choi, I. (1999). Testing the Random Walk Hypothesis for Real Exchange Rates. <em>Journal of Applied Econometrics</em>, 14(3), 293–308. <a href="https://doi.org/10.1002/(SICI)1099-1255(199905/06)14:3&lt;293::AID-JAE503&gt;3.0.CO;2-5" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1002/(SICI)1099-1255(199905/06)14:3&lt;293::AID-JAE503&gt;3.0.CO;2-5</a>
  10. Chu, J., Zhang, Y., &amp; Chan, S. (2019). The Adaptive Market Hypothesis in the High Frequency Cryptocurrency Market. <em>International Review of Financial Analysis</em>, 64(C), 221–231. <a href="https://doi.org/10.1016/j.irfa.2019.05.008" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.irfa.2019.05.008</a>
  11. Escanciano, J. C., &amp; Lobato, I. N. (2009). An Automatic Portmanteau Test for Serial Correlation. <em>Journal of Econometrics</em>, 151(2), 140–149. <a href="https://doi.org/10.1016/j.jeconom.2009.03.001" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.jeconom.2009.03.001</a>
  12. Fama, E. F. (1965). The Behaviour of Stock Market Prices. <em>Journal of Business</em>, 38(1), 34–105. <a href="https://doi.org/10.1086/294743" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1086/294743</a>
  13. Fieberg, C., Liedtke, G., Poddig, T., Walker, T., &amp; Zaremba, A. (2024). A Trend Factor for the Cross-Section of Cryptocurrency Returns. <em>Journal of Financial and Quantitative Analysis</em>. <a href="https://dx.doi.org/10.2139/ssrn.4601972" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://dx.doi.org/10.2139/ssrn.4601972</a>
  14. Hawaldar, I. T., Mathukutti, R., &amp; Dsouza, L. J. (2019). Testing the Weak Form of Efficiency of Cryptocurrencies: A Case Study of Bitcoin and Litecoin. <em>International Journal of Scientific &amp; Technology Research</em>, 8(9), 2301–2305.
  15. Hu, Y., Valera, H. G. A., &amp; Oxley, L. (2019). Market Efficiency of the Top Market-Cap Cryptocurrencies: Further Evidence From a Panel Framework. <em>Finance Research Letters</em>, 31(C), 138–145. <a href="https://doi.org/10.1016/j.frl.2019.04.012" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2019.04.012</a>
  16. Kang, H.-J., Lee, S.-G., &amp; Park, S.-Y. (2022) Information Efficiency in the Cryptocurrency Market: The Efficient-Market Hypothesis. <em>Journal of Computer Information Systems</em>, 62(3), 622–631. <a href="https://doi.org/10.1080/08874417.2021.1872046" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1080/08874417.2021.1872046</a>
  17. Khuntia, S., &amp; Pattanayak, J. K. (2018). Adaptive Market Hypothesis and Evolving Predictability of Bitcoin. <em>Economics Letters</em>, 167, 26–28. <a href="https://doi.org/10.1016/j.econlet.2018.03.005" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.econlet.2018.03.005</a>
  18. Khursheed, A., Naeem, M., Ahmed, S., &amp; Mustafa, F. (2020). Adaptive Market Hypothesis: An Empirical Analysis of Time-Varying Market Efficiency of Cryptocurrencies. <em>Cogent Economics and Finance</em>, 8(1). <a href="https://doi.org/10.1080/23322039.2020.1719574" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1080/23322039.2020.1719574</a>
  19. Kim, J. H. (2009). Automatic Variance Ratio Test Under Conditional Heteroskedasticity. <em>Finance Research Letters</em>, 6(3), 179–185. <a href="https://doi.org/10.1016/j.frl.2009.04.003" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2009.04.003</a>
  20. Kristjanpoller, W., Nekhili, R., &amp; Bouri, E. (2024). Ethereum Futures and the Efficiency of Cryptocurrency Spot Markets. <em>Physica A: Statistical Mechanics and its Applications</em>, 654, 130161. <a href="https://doi.org/10.1016/j.physa.2024.130161" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.physa.2024.130161</a>
  21. Linton, O. (2019). <em>Financial Econometrics: Models and Methods</em>. Cambridge: Cambridge University Press. <a href="https://doi.org/10.1017/9781316819302" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1017/9781316819302</a>
  22. Lo, A. W. (2004). The Adaptive Markets Hypothesis. <em>Journal of Portfolio Management</em>, 30(5), 15–29. <a href="https://doi.org/10.3905/jpm.2004.442611" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.3905/jpm.2004.442611</a>
  23. Lo, A. W. (2005). Reconciling Efficient Markets with Behavioral Finance: The Adaptive Markets Hypothesis. <em>Journal of Investment Consulting</em>, 7(2), 21–44.
  24. López-Martín, C., Muela, S. B., &amp; Arguedas, R. (2021). Efficiency in Cryptocurrency Markets: New Evidence. <em>Eurasian Economic Review</em>, 11(3), 403–431. <a href="https://doi.org/10.1007/s40822-021-00182-5" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1007/s40822-021-00182-5</a>
  25. Meng, K., &amp; Khan, K. (2023). Is Cryptocurrency Efficient? A High-Frequency Asymmetric Multifractality Analysis. <em>Computational Economics</em>, 63, 2225–2246. <a href="https://doi.org/10.1007/s10614-023-10402-6" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1007/s10614-023-10402-6</a>
  26. Mensi, W., Lee, Y.-J., Al-Yahyaee, K. H., Sensoy, A., &amp; Yoon, S.-M. (2019). Intraday Downward/Upward Multifractality and Long Memory in Bitcoin and Ethereum Markets: An Asymmetric Multifractal Detrended Fluctuation Analysis. <em>Finance Research Letters</em>, 31, 19–25. <a href="https://doi.org/10.1016/j.frl.2019.03.029" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2019.03.029</a>
  27. Mokni, K., Montasser, G. E., Ajmi, A. N., &amp; Bouri, E. (2024). On the Efficiency and its Drivers in the Cryptocurrency Market: The Case of Bitcoin and Ethereum. <em>Financial Innovation</em>, 10, 39. <a href="https://doi.org/10.1186/s40854-023-00566-3" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1186/s40854-023-00566-3</a>
  28. Nadarajah, S., &amp; Chu, J. (2017). On the Inefficiency of Bitcoin. <em>Economics Letters</em>, 150(C), 6–9. <a href="https://doi.org/10.1016/j.econlet.2016.10.033" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.econlet.2016.10.033</a>
  29. Noda, A. (2020). On the Evolution of Cryptocurrency Market Efficiency. <em>Applied Economic Letters</em>, 28(6), 433–439. <a href="https://doi.org/10.1080/13504851.2020.1758617" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1080/13504851.2020.1758617</a>
  30. Okorie, D. I., Bouri, E., &amp; Mazur, M. (2024). NFTs versus Conventional Cryptocurrencies: A Comparative Analysis of Market Efficiency Around COVID-19 and the Russia-Ukraine Conflict. <em>The Quarterly Review of Economics and Finance</em>, 95, 126–151. <a href="https://doi.org/10.1016/j.qref.2024.03.001" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.qref.2024.03.001</a>
  31. Palamalai, S., Kumar, K. K., &amp; Maity, B. (2021). Testing the Random Walk Hypothesis for Leading Cryptocurrencies. <em>Borsa Istanbul Review</em>, 21(3), 256–268.
  32. Polyzos, E., Rubbaniy, G., &amp; Mazur, M. (2024). Efficient Market Hypothesis on the Blockchain: A Social-Media-Based Index for Cryptocurrency Efficiency. <em>The Financial Review</em>, 59(3), 807–829. <a href="https://doi.org/10.1111/fire.12387" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1111/fire.12387</a>
  33. Samuelson, P. A. (1965). Proof That Properly Anticipated Prices Fluctuate Randomly. <em>Industrial Management Review</em>, 6, 41–49.
  34. Sensoy, A. (2019). The Inefficiency of Bitcoin Revisited: A High-Frequency Analysis with Alternative Currencies. <em>Finance Research Letters</em>, 28(C), 68–73. <a href="https://doi.org/10.1016/j.frl.2018.04.002" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2018.04.002</a>
  35. Tiwari, A. K., Jana, R. K., Das, D., &amp; Roubaud, D. (2018). Informational Efficiency of Bitcoin—An Extension. <em>Economics Letters</em>, 163, 106–109. <a href="https://doi.org/10.1016/j.econlet.2017.12.006" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.econlet.2017.12.006</a>
  36. Tran, V. L., &amp; Leirvik, T. (2020). Efficiency in the Markets of Crypto-Currencies. <em>Finance Research Letters</em>, 35(C). <a href="https://doi.org/10.1016/j.frl.2019.101382" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2019.101382</a>
  37. Urquhart. (2016). The Inefficiency of Bitcoin. <em>Economics Letters</em>, 148(C), 80–82. <a href="https://doi.org/10.1016/j.econlet.2016.09.019" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.econlet.2016.09.019</a>
  38. Verma, R., Sharma, D., &amp; Sam, S. (2022). Testing of Random Walk Hypothesis in the Cryptocurrency Market. <em>FIIB Business Review</em>, 1–9. <a href="https://doi.org/10.1177/23197145221101238" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1177/23197145221101238</a>
  39. Yi, E., Yang, B., Jeong, M., Sohn, S., &amp; Ahn, K. (2023). Market Efficiency of Cryptocurrency: Evidence From the Bitcoin Market. <em>Scientific Reports</em>, 13, 4789. <a href="https://doi.org/10.1038/s41598-023-31618-4" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1038/s41598-023-31618-4</a>
  40. Yonghong, J., He, N., &amp; Weihua, R. (2018). Time-Varying Long-Term Memory in Bitcoin Market. <em>Finance Research Letters</em>, 25(C), 280–284. <a href="https://doi.org/10.1016/j.frl.2017.12.009" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.frl.2017.12.009</a>
  41. Zargar, F. N., &amp; Kumar, D. (2019). Informational Inefficiency of Bitcoin: A Study Based on High-Frequency Data. <em>Research in International Business and Finance</em>, 47, 344–353. <a href="https://doi.org/10.1016/j.ribaf.2018.08.008" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.ribaf.2018.08.008</a>
  42. Zhang, W., Wang, P., Li, X., &amp; Shen, D. (2018). The Inefficiency of Cryptocurrency and its Cross-Correlation With Dow Jones Industrial Average. <em>Physica A: Statistical Mechanics and its Applications</em>, 510, 658–670. <a href="https://doi.org/10.1016/j.physa.2018.07.032" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1016/j.physa.2018.07.032</a>
  43. Zhang, Y., Chan, S., Chu, J., &amp; Shih, S. (2023) The Adaptive Market Hypothesis of Decentralized Finance (DeFi), <em>Applied Economics</em>, 55(42), 4975–4989. <a href="https://doi.org/10.1080/00036846.2022.2133895" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.1080/00036846.2022.2133895</a>
DOI: https://doi.org/10.2478/ceej-2025-0003 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001
Language: English
Page range: 34 - 48
Published on: Feb 2, 2025
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Jacek Karasiński, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 License.