[1] Aggarwal, Divya. 2019. “Do Bitcoins Follow a Random Walk Model?” Research in Economics 73 (1): 15–22.
https://doi.org/10.1016/j.rie.2019.01.002.

[2] Alexiadou, Monica, Emmanouil Sofianos, Periklis Gogas, and Theophilos Papadimitriou. 2023. “Cryptocurrencies and Long-Range Trends.” International Journal of Financial Studies 11 (1): 40.
https://doi.org/10.3390/ijfs11010040.

[3] Anamika, Madhumita Chakraborty, and Sowmya Subramaniam. 2023. “Does Sentiment Impact Cryptocurrency?” Journal of Behavioral Finance 24 (2): 202–18.
https://doi.org/10.1080/15427560.2021.1950723.

[4] Apopo, Natalya, and Andrew Phiri. 2021. “On the (in)Efficiency of Cryptocurrencies: Have They Taken Daily or Weekly Random Walks?” Heliyon 7 (4): e06685.
https://doi.org/10.1016/j.heliyon.2021.e06685.

[5] Bariviera, Aurelio F. 2017. “The Inefficiency of Bitcoin Revisited: A Dynamic Approach.” Economics Letters 161 (December): 1–4.
https://doi.org/10.1016/j.econlet.2017.09.013.

[6] Campbell, John Y., Andrew W. Lo, A. Craig MacKinlay, and Robert F. Whitelaw. 1998. “The Econometrics of Financial Markets.” Macroeconomic Dynamics 2 (4): 559–62.

[7] Challa, Madhavi Latha, Venkataramanaiah Malepati, and Siva Nageswara Rao Kolusu. 2020. “S&P BSE Sensex and S&P BSE IT Return Forecasting Using ARIMA.” Financial Innovation 6 (1): 47.
https://doi.org/10.1186/s40854-020-00201-5.

[8] Escanciano, J. Carlos, and Carlos Velasco. 2006. “Generalized Spectral Tests for the Martingale Difference Hypothesis.” Journal of Econometrics 134 (1): 151–85.

[9] Fama, Eugene F. 1965. “The Behavior of Stock-Market Prices.” The Journal of Business 38 (1): 34–105.

[10] ———. 1970. “Efficient Capital Markets: A Review of Theory and Empirical Work.” The Journal of Finance 25 (2): 383–417.

[11] Jarque, Carlos M., and Anil K. Bera. 1980. “Efficient Tests for Normality, Homoscedasticity and Serial Independence of Regression Residuals.” Economics Letters 6 (3): 255–59.
https://doi.org/10.1016/0165-1765(80)90024-5.

[12] Kang, Ho-Jun, Sang-Gun Lee, and Soo-Yong Park. 2022. “Information Efficiency in the Cryptocurrency Market:The Efficient-Market Hypothesis.” Journal of Computer Information Systems 62 (3): 622–31.
https://doi.org/10.1080/08874417.2021.1872046.

[13] Karaömer, Yunus, and Songül Kakilli Acaravci. 2023. “Adaptive Market Hypothesis: Evidence From the Cryptocurrency Market” 16 (1): 125–38.

[14] Kayal, Parthajit, and G. Balasubramanian. 2021. “Excess Volatility in Bitcoin: Extreme Value Volatility Estimation.” IIM Kozhikode Society & Management Review 10 (2): 222–31.
https://doi.org/10.1177/2277975220987686.

[15] Keshari Jena, Sangram, Aviral Kumar Tiwari, Buhari Dogan, and Shawkat Hammoudeh. 2022. “Are the Top Six Cryptocurrencies Efficient? Evidence from Time-varying Long Memory.” International Journal of Finance & Economics 27 (3): 3730–40.
https://doi.org/10.1002/ijfe.2347.

[16] Khuntia, Sashikanta, and J. K. Pattanayak. 2020. “Evolving Efficiency of Exchange Rate Movement: An Evidence from Indian Foreign Exchange Market.” Global Business Review 21 (4): 956–69.
https://doi.org/10.1177/0972150919856996.

[17] Kurihara, Yutaka, and Akio Fukushima. 2017. “The Market Efficiency of Bitcoin: A Weekly Anomaly Perspective.” Journal of Applied Finance and Bankin 7 (3): 8.

[18] Kyriazis. 2019. “A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets.” Journal of Risk and Financial Management 12 (2): 67.
https://doi.org/10.3390/jrfm12020067.

[19] Lazar, Dorina, Alexandru Todea, and Diana Filip. 2012. “Martingale Difference Hypothesis and Financial Crisis: Empirical Evidence from European Emerging Foreign Exchange Markets.” Economic Systems 36 (3): 338–50.

[20] Liu, Yukun, and Aleh Tsyvinski. 2021. “Risks and Returns of Cryptocurrency.” The Review of Financial Studies 34 (6): 2689–2727.

[21] Lo, Andrew W., and A. Craig MacKinlay. 1989. “The Size and Power of the Variance Ratio Test in Finite Samples: A Monte Carlo Investigation.” Journal of Econometrics 40 (2): 203–38.

[22] Lupu, Radu, and Catalina Maria Popa. 2022. “High Frequency Market Efficiency Test for Cryptocurrency.” In ”30 Years of Inspiring Academic Economic Research – From the Transition to Market Economy to the Interlinked Crises of 21st Century”, by Askenasy Jean Jacques, 204–17. Sciendo.
https://doi.org/10.2478/9788366675261-015.

[23] Magner, Nicolás, and Nicolás Hardy. 2022. “Cryptocurrency Forecasting: More Evidence of the Meese-Rogoff Puzzle.” Mathematics 10 (13): 2338.
https://doi.org/10.3390/math10132338.

[24] Mahalwala, Dr Rachna. 2022. “Examining the Weak-Form Market Efficiency in Cryptocurrency Market.” International Journal of Advances in Engineering and Management (IJAEM) 4 (5): 1328-1335.

[25] Mallesha, L., and H. N. Archana. 2023. “Testing of Random Walk Hypothesis in The Cryptocurrency Market: After Declaration of Global Pandemic.” Research Bulletin 49 (1): 160–76.

[26] ———. 2024. “Indian Stock Market Efficiency: Evidence from Banking Sector.” The Chartered Accountant 72 (9).

[27] Nadarajah, Saralees, and Jeffrey Chu. 2017. “On the Inefficiency of Bitcoin.” Economics Letters 150 (January): 6–9.
https://doi.org/10.1016/j.econlet.2016.10.033.

[28] Patel, Menesh S. 2022. “Fraud on the Crypto Market.” Harvard Journal of Law & Technology 36 (1).
https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/hjlt36§ion=7.

[29] Pathak, Rajesh, Ranjan Das Gupta, Cleiton Guollo Taufemback, and Aviral Kumar Tiwari. 2020. “Testing the Efficiency of Metal’s Market: New Evidence from a Generalized Spectral Test.” Studies in Economics and Finance 37 (2): 311–21.
https://doi.org/10.1108/SEF-07-2019-0253.

[30] Urquhart, Andrew. 2016. “The Inefficiency of Bitcoin.” Economics Letters 148 (November): 80–82. https://doi.org/10.1016/j.econlet.2016.09.019.

[31] Verma, Ruchita, Dhanraj Sharma, and Shiney Sam. 2022. “Testing of Random Walk Hypothesis in the Cryptocurrency Market.” FIIB Business Review, 23197145221101238.

[32] Yi, Eojin, Biao Yang, Minhyuk Jeong, Sungbin Sohn, and Kwangwon Ahn. 2023. “Market Efficiency of Cryptocurrency: Evidence from the Bitcoin Market.” Scientific Reports 13 (1): 4789.
https://doi.org/10.1038/s41598-023-31618-4.