275
Views
2
CrossRef citations to date
0
Altmetric
Research Article

Informational inefficiency on bitcoin futures

ORCID Icon, &
Pages 642-667 | Received 29 Jan 2022, Accepted 17 May 2023, Published online: 28 May 2023

References

  • Abdi, F., and A. Ranaldo. 2017. “A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices.” The Review of Financial Studies 30 (12): 4437–4480. doi:10.1093/rfs/hhx084
  • Acharya, V. V., L. A. Lochstoer, and T. Ramadorai. 2013. “Limits to Arbitrage and Hedging: Evidence from Commodity Markets.” Journal of Financial Economics 109: 441–465. doi:10.1016/j.jfineco.2013.03.003
  • Akbas, F., W. J. Armstrong, S. Sorescu, and A. Subrahmanyam. 2016. “Capital Market Efficiency and Arbitrage Efficacy.” Journal of Financial and Quantitative Analysis 51 (2): 387–413. doi:10.1017/S0022109016000223
  • Aleti, S., and B. Mizrach. 2021. “Bitcoin Spot and Futures Market Microstructure.” Journal of Futures Markets 41: 194–225. doi:10.1002/fut.22163
  • Alexander, C., J. Choi, H. Park, and S. Sohn. 2020. “BitMEX Bitcoin Derivatives: Price Discovery, Informational Efficiency, and Hedging Effectiveness.” Journal of Futures Markets 40: 23–43. doi:10.1002/fut.22050
  • Alexander, C., and M. Dakos. 2020. “A Critical Investigation of Cryptocurrency Data and Analysis.” Quantitative Finance 20 (2): 173–188. doi:10.1080/14697688.2019.1641347
  • Alexander, C., and D. F. Heck. 2020. “Price Discovery in Bitcoin: The Impact of Unregulated Markets.” Journal of Financial Stability 50: 100776.
  • Alvarez-Ramirez, J., and E. Rodriguez. 2021a. “A Singular Value Decomposition Approach for Testing the Efficiency of Bitcoin and Ethereum Markets.” Economics Letters 206: 109997. doi:10.1016/j.econlet.2021.109997
  • Alvarez-Ramirez, J., and E. Rodriguez. 2021b. “A Singular Value Decomposition Entropy Approach for Testing Stock Market Efficiency.” Physica A: Statistical Mechanics and its Applications 583: 126337. doi:10.1016/j.physa.2021.126337
  • Alvarez-Ramirez, J., E. Rodriguez, and J. Alvarez. 2012. “A Multiscale Entropy Approach for Market Efficiency.” International Review of Financial Analysis 21: 64–69. doi:10.1016/j.irfa.2011.12.001
  • Amihud, Y. 2002. “Illiquidity and Stock Returns: Cross-Section and Time-Series Effects.” Journal of Financial Markets 5 (1): 31–56. doi:10.1016/S1386-4181(01)00024-6
  • Assaf, A., A. Bhandari, H. Charif, and E. Demir. 2022. “Multivariate Long Memory Structure in the Cryptocurrency Market: The Impact of COVID-19.” International Review of Financial Analysis 82: 102132. doi:10.1016/j.irfa.2022.102132
  • Assaf, A., L. Kristoufek, E. Demir, and S. K. Mitra. 2021. “Market Efficiency in the art Markets Using a Combination of Long Memory, Fractal Dimension, and Approximate Entropy Measures.” Journal of International Financial Markets, Institutions and Money 71: 101312. doi:10.1016/j.intfin.2021.101312
  • Auer, R., and D. Tercero-Lucas. 2021. “Distrust or Speculation? The Socioeconomic Drivers of U.S. Cryptocurrency Investments.” BIS Working Papers No 951.
  • Bains, P., M. Diaby, D. Drakopoulos, J. Faltermeier, F. Grinberg, E. Papageorgiou, et al. 2021. Global Financial Stability Report, Chapter 2: The Crypto Ecosystem and Financial Stability Challenges. Washington, DC: International Monetary Fund.
  • Baker, M., and J. Wurgler. 2006. “Investor Sentiment and the Cross-Section of Stock Returns.” The Journal of Finance 61: 1645–1680. doi:10.1111/j.1540-6261.2006.00885.x
  • Baker, M., and J. Wurgler. 2007. “Investor Sentiment in the Stock Market.” Journal of Economic Perspectives 21: 129–151. doi:10.1257/jep.21.2.129
  • Bakshi, G., X. Gao, and A. G. Rossi. 2019. “Understanding the Sources of Risk Underlying the Cross Section of Commodity Returns.” Management Science 65 (2): 619–641. doi:10.1287/mnsc.2017.2840
  • Bariviera, A. F. 2017. “The Inefficiency of Bitcoin Revisited: A Dynamic Approach.” Economics Letters 161: 1–4. doi:10.1016/j.econlet.2017.09.013
  • Baur, D. G., and T. Dimpfl. 2019. “Price Discovery in Bitcoin Spot or Futures?” Journal of Futures Markets 39: 803–817. doi:10.1002/fut.22004
  • Baur, D. G., K. Hong, and A. D. Lee. 2018. “Bitcoin: Medium of Exchange or Speculative Assets?” Journal of International Financial Markets, Institutions and Money 54: 177–189. doi:10.1016/j.intfin.2017.12.004
  • Benedetto, F., G. Giunta, and L. Mastroeni. 2016. “On the Predictability of Energy Commodity Markets by an Entropy-Based Computational Method.” Energy Economics 54: 302–312. doi:10.1016/j.eneco.2015.12.009
  • Bogdan, D. I., Ş. M. Dima, and I. O. Roxana. 2021. “Remarks on the Behaviour of Financial Market Efficiency During the COVID-19 Pandemic. The Case of VIX.” Finance Research Letters 43: 101967. doi:10.1016/j.frl.2021.101967
  • Bohl, M. T., A. Pütz, and C. Sulewski. 2021. “Speculation and the Informational Efficiency of Commodity Futures Markets.” Journal of Commodity Markets 23: 100159. doi:10.1016/j.jcomm.2020.100159
  • Bonnier, J. B. 2021. “Speculation and Informational Efficiency in Commodity Futures Markets.” Journal of International Money and Finance 117: 102457. doi:10.1016/j.jimonfin.2021.102457
  • Bouri, E., L. A. Gil-Alana, R. Gupta, and D. Roubaud. 2019. “Modelling Long Memory Volatility in the Bitcoin Market: Evidence of Persistence and Structural Breaks.” International Journal of Finance & Economics 24 (1): 412–426. doi:10.1002/ijfe.1670
  • Brauneis, A., R. Mestel, R. Riordan, and E. Riordan. 2021. “How to Measure the Liquidity of Cryptocurrency Markets?” Journal of Banking & Finance 124: 106041. doi:10.1016/j.jbankfin.2020.106041
  • Caraiani, P. 2014. “The Predictive Power of Singular Value Decomposition Entropy for Stock Market Dynamics.” Physica A: Statistical Mechanics and its Applications 393: 571–578. doi:10.1016/j.physa.2013.08.071
  • CFBenchmarks. 2022. “CF Benchmarks Adds LMAX Digital as Constituent Exchange for CME CF Bitcoin Reference Rate, and CME CF Ether-Dollar Reference Rate.” CFBenchmarks, March 31. https://blog.cfbenchmarks.com/cf-benchmarks-adds-lmax-digital-as-constituent-exchange-for-cme-cf-bitcoin-reference-rate-and-cme-cf-ether-dollar-reference-rate/.
  • Cheah, J. E. T., D. Luo, Z. Zhang, and M. C. Sung. 2022. “Predictability of Bitcoin Returns.” The European Journal of Finance 28(1): 66–85.
  • Cheah, E. T., T. Mishra, M. Parhi, and Z. Zhang. 2018. “Long Memory Interdependency and Inefficiency in Bitcoin Markets.” Economics Letters 167: 18–25. doi:10.1016/j.econlet.2018.02.010
  • Cheng, I. H., A. Kirilenko, and W. Xiong. 2015. “Convective Risk Flows in Commodity Futures Markets.” Review of Finance 19: 1733–1781. doi:10.1093/rof/rfu043
  • Chordia, T., R. Roll, and A. Subrahmanyam. 2008. “Liquidity and market efficiency.” Journal of Financial Economics 87 (2): 249–268. doi:10.1016/j.jfineco.2007.03.005
  • Chordia, T., R. Roll, and A. Subrahmanyam. 2011. “Recent Trends in Trading Activity and Market Quality.” Journal of Financial Economics 101 (2): 243–263. doi:10.1016/j.jfineco.2011.03.008
  • Chu, J., Y. Zhang, and S. Chan. 2019. “The Adaptive Market Hypothesis in the High Frequency Cryptocurrency Market.” International Review of Financial Analysis 64: 221–231. doi:10.1016/j.irfa.2019.05.008
  • Chung, D., and K. Hrazdil. 2010. “Liquidity and Market Efficiency: A Large Sample Study.” Journal of Banking & Finance 34: 2346–2357. doi:10.1016/j.jbankfin.2010.02.021
  • Corbet, S., C. Larkin, B. M. Lucey, A. Meegan, and L. Yarovaya. 2020. “The Impact of Macroeconomic News on Bitcoin Returns.” The European Journal of Finance 26 (14): 1396–1416. doi:10.1080/1351847X.2020.1737168
  • Corbet, S., B. Lucey, M. Peat, and S. Vigne. 2018. “Bitcoin Futures—What Use are They?” Economics Letters 172: 23–27. doi:10.1016/j.econlet.2018.07.031
  • Corwin, S. A., and P. Schultz. 2012. “A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices.” The Journal of Finance 67 (2): 719–760. doi:10.1111/j.1540-6261.2012.01729.x
  • David, S. A., C. M. Inacio Jr, D. D. Quintino, and J. A. Machado. 2020. “Measuring the Brazilian Ethanol and Gasoline Market Efficiency Using DFA-Hurst and Fractal Dimension.” Energy Economics 85: 104614. doi:10.1016/j.eneco.2019.104614
  • De Roon, F. A., T. E. Nijman, and C. Veld. 2000. “Hedging Pressure Effects in Futures Markets.” The Journal of Finance 55 (3): 1437–1456. doi:10.1111/0022-1082.00253
  • Diniz-Maganini, N., A. A. Rasheed, and H. H. Sheng. 2021. “Exchange Rate Regimes and Price Efficiency: Empirical Examination of the Impact of Financial Crisis.” Journal of International Financial Markets, Institutions and Money 73: 101361. doi:10.1016/j.intfin.2021.101361
  • Domínguez, M. A., and I. N. Lobato. 2003. “Testing the Martingale Difference Hypothesis.” Econometric Reviews 22 (4): 351–377. doi:10.1081/ETC-120025895
  • Duan, K., Y. Gao, T. Mishra, and S. Satchell. 2023. “Efficiency Dynamics Across Segmented Bitcoin Markets: Evidence from a Decomposition Strategy.” Journal of International Financial Markets, Institutions and Money 83: 101742. doi:10.1016/j.intfin.2023.101742
  • Duan, K., Z. Li, A. Urquhart, and J. Ye. 2021. “Dynamic Efficiency and Arbitrage Potential in Bitcoin: A Long-Memory Approach.” International Review of Financial Analysis 75: 101725. doi:10.1016/j.irfa.2021.101725
  • Easley, D., M. O’Hara, and S. Basu. 2019. “From Mining to Markets: The Evolution of Bitcoin Transaction Fees.” Journal of Financial Economics 134 (1): 91–109. doi:10.1016/j.jfineco.2019.03.004
  • El Montasser, G., L. Charfeddine, and A. Benhamed. 2022. “COVID-19, Cryptocurrencies Bubbles and Digital Market Efficiency: Sensitivity and Similarity Analysis.” Finance Research Letters 46: 102362. doi:10.1016/j.frl.2021.102362
  • Escanciano, J. C., and I. N. Lobato. 2009. “An Automatic Portmanteau Test for Serial Correlation.” Journal of Econometrics 151 (2): 140–149. doi:10.1016/j.jeconom.2009.03.001
  • Escanciano, J. C., and C. Velasco. 2006. “Generalized Spectral Tests for the Martingale Difference Hypothesis.” Journal of Econometrics 134 (1): 151–185. doi:10.1016/j.jeconom.2005.06.019
  • Fama, E. F. 1965. “The Behavior of Stock-Market Prices.” The Journal of Business 38 (1): 34–105. doi:10.1086/294743
  • Fama, E. F. 1970. “Efficient Capital Markets: A Review of Theory and Empirical Work.” The Journal of Finance 25 (2): 383–417. doi:10.2307/2325486
  • Foley, S., J. R. Karlsen, and T. J. Putniņš. 2019. “Sex, Drugs, and Bitcoin: How Much Illegal Activity is Financed Through Cryptocurrencies?” The Review of Financial Studies 32 (5): 1798–1853. doi:10.1093/rfs/hhz015
  • Geweke, J., and S. Porter-Hudak. 1983. “The Estimation and Application of Long Memory Time Series Models.” Journal of Time Series Analysis 4: 221–238. doi:10.1111/j.1467-9892.1983.tb00371.x
  • Gneiting, T., H. Sevcikova, and D. B. Percival. 2012. “Estimators of Fractal Dimension: Assessing the Roughness of Time Series and Spatial Data.” Statistical Science 27 (2): 247–277. doi:10.1214/11-STS370
  • Godbole, O. 2020. “CME’s Rise in Bitcoin Futures Rankings Signals Growing Institutional Interest.” CoinDesk, October 23. https://www.coindesk.com/markets/2020/10/23/cmes-rise-in-bitcoin-futures-rankings-signals-growing-institutional-interest/.
  • Griffin, J. M., and A. Shams. 2020. “Is Bitcoin Really Untethered?” The Journal of Finance 75 (4): 1913–1964. doi:10.1111/jofi.12903
  • Grobys, K., and J. Junttila. 2021. “Speculation and Lottery-Like Demand in Cryptocurrency Markets.” Journal of International Financial Markets, Institutions and Money 71: 101289. doi:10.1016/j.intfin.2021.101289
  • Gronwald, M. 2019. “Is Bitcoin a Commodity? On Price Jumps, Demand Shocks, and Certainty of Supply.” Journal of International Money and Finance 97: 86–92. doi:10.1016/j.jimonfin.2019.06.006
  • Gu, R., W. Xiong, and X. Li. 2015. “Does the Singular Value Decomposition Entropy Have Predictive Power for Stock Market? — Evidence from the Shenzhen Stock Market.” Physica A: Statistical Mechanics and its Applications 439: 103–113. doi:10.1016/j.physa.2015.07.028
  • Guo, Z.-Y. 2021a. “Price Volatilities of Bitcoin Futures.” Finance Research Letters 43: 102022.
  • Guo, Z.-Y. 2021b. “Risk Management of Bitcoin Futures with GARCH Models.” Finance Research Letters 45: 102197.
  • Hattori, T., and R. Ishida. 2021. “The Relationship Between Arbitrage in Futures and Spot Markets and Bitcoin Price Movements: Evidence from the Bitcoin Markets.” Journal of Futures Markets 41: 105–114. doi:10.1002/fut.22171
  • Hoang, L. T., and D. G. Baur. 2020. “Forecasting Bitcoin Volatility: Evidence from the Options Market.” Journal of Futures Markets 40: 1584–1602. doi:10.1002/fut.22144
  • Hung, J.-C., H.-C. Liu, and J. Yang. 2021. “Trading Activity and Price Discovery in Bitcoin Futures Markets.” Journal of Empirical Finance 62: 107–120. doi:10.1016/j.jempfin.2021.03.001
  • Ibikunle, G., A. Gregoriou, A. G. Hoepner, and M. Rhodes. 2016. “Liquidity and Market Efficiency in the World's Largest Carbon Market.” The British Accounting Review 48: 431–447. doi:10.1016/j.bar.2015.11.001
  • ISDA. 2021. “First Steps to Crypto Derivatives Standards.” ISDA, September 30.
  • Jalan, A., R. Matkovskyy, and A. Urquhart. 2021. “What Effect Did the Introduction of Bitcoin Futures Have on the Bitcoin Spot Market.” The European Journal of Finance 27(13): 1251–1281.
  • Jiang, Y., H. Nie, and W. Ruan. 2018. “Time-Varying Long-Term Memory in Bitcoin Market.” Finance Research Letters 25: 280–284. doi:10.1016/j.frl.2017.12.009
  • Jiang, Y., L. Wu, G. Tian, and H. Nie. 2021. “Do Cryptocurrencies Hedge Against EPU and the Equity Market Volatility During COVID-19? – New Evidence from Quantile Coherency Analysis.” Journal of International Financial Markets, Institutions and Money 72: 101324. doi:10.1016/j.intfin.2021.101324
  • Jo, H., H. Park, and H. Shefrin. 2020. “Bitcoin and Sentiment.” Journal of Futures Markets 40: 1861–1879. doi:10.1002/fut.22156
  • Kalyvas, A., Z. Li, P. Papakyriakou, and A. Sakkas. 2021. “If You Feel Good, I Feel Good! The Mediating Effect of Behavioral Factors on the Relationship Between Industry Indices and Bitcoin Returns.” The European Journal of Finance, 1–12. doi:10.1080/1351847X.2021.1976665
  • Kang, W., K. G. Rouwenhorst, and K. Tang. 2020. “A Tale of Two Premiums: The Role of Hedgers and Speculators in Commodity Futures Markets.” The Journal of Finance 75 (1): 377–417. doi:10.1111/jofi.12845
  • Kang, W., K. G. Rouwenhorst, and K. Tang. 2021. Crowding and Factor Returns. doi:10.2139/SSRN.3803954.
  • Kapar, B., and J. Olmo. 2019. “An Analysis of Price Discovery Between Bitcoin Futures and Spot Markets.” Economics Letters 174: 62–64. doi:10.1016/j.econlet.2018.10.031
  • Karaa, R., S. Slim, J. W. Goodell, A. Goyal, and V. Kallinterakis. 2021. “Do Investors Feedback Trade in the Bitcoin—and Why?” The European Journal of Finance, 1–21. doi:10.1080/1351847X.2021.1973054
  • Keshari Jena, S., A. K. Tiwari, B. Doğan, and S. Hammoudeh. 2022. “Are the Top Six Cryptocurrencies Efficient? Evidence from Time-Varying Long Memory.” International Journal of Finance & Economics 27 (3): 3730–3740. doi:10.1002/ijfe.2347
  • Khuntia, S., and J. Pattanayak. 2018. “Adaptive Market Hypothesis and Evolving Predictability of Bitcoin.” Economics Letters 167: 26–28. doi:10.1016/j.econlet.2018.03.005
  • Khuntia, S., and J. K. Pattanayak. 2020. “Adaptive Long Memory in Volatility of Intra-Day Bitcoin Returns and the Impact of Trading Volume.” Finance Research Letters 32: 101077. doi:10.1016/j.frl.2018.12.025
  • Kim, J. H. 2009. “Automatic Variance Ratio Test under Conditional Heteroskedasticity.” Finance Research Letters 6 (3): 179–185. doi:10.1016/j.frl.2009.04.003
  • Kim, W., J. Lee, and K. Kang. 2020. “The Effects of the Introduction of Bitcoin Futures on the Volatility of Bitcoin Returns.” Finance Research Letters 33: 101204. doi:10.1016/j.frl.2019.06.002
  • Köchling, G., J. Müller, and P. Posch. 2019. “Does the Introduction of Futures Improve the Efficiency of Bitcoin?.” Finance Research Letters 30: 367–370. doi:10.1016/j.frl.2018.11.006
  • Kristoufek, L. 2018. “On Bitcoin Markets (In)efficiency and Its Evolution.” Physica A: Statistical Mechanics and its Applications 503: 257–262. doi:10.1016/j.physa.2018.02.161
  • Kristoufek, L., and M. Vosvrda. 2013. “Measuring Capital Market Efficiency: Global and Local Correlations Structure.” Physica A: Statistical Mechanics and its Applications 392: 184–193. doi:10.1016/j.physa.2012.08.003
  • Kristoufek, L., and M. Vosvrda. 2014a. “Commodity Futures and Market Efficiency.” Energy Economics 42: 50–57. doi:10.1016/j.eneco.2013.12.001
  • Kristoufek, L., and M. Vosvrda. 2014b. “Measuring Capital Market Efficiency: Long-Term Memory, Fractal Dimension and Approximate Entropy.” The European Physical Journal B 87 (7): 162. doi:10.1140/epjb/e2014-50113-6
  • Kristoufek, L., and M. Vosvrda. 2019. “Cryptocurrencies Market Efficiency Ranking: Not so Straightforward.” Physica A: Statistical Mechanics and its Applications 531: 120853. doi:10.1016/j.physa.2019.04.089
  • Kyle, A. S., and A. A. Obizhaeva. 2016. “Market Microstructure Invariance: Empirical Hypotheses.” Econometrica 84 (4): 1345–1404. doi:10.3982/ECTA10486
  • Lee, A. D., M. Li, and H. Zheng. 2020. “Bitcoin: Speculative Asset or Innovative Technology?” Journal of International Financial Markets, Institutions and Money 67: 101209. doi:10.1016/j.intfin.2020.101209
  • Lim, K. P., and R. D. Brooks. 2011. “The Evolution of Stock Market Efficiency Over Time: A Survey of the Empirical Literature.” Journal of Economic Surveys 25 (1): 69–108. doi:10.1111/j.1467-6419.2009.00611.x
  • Liu, Q., Q. Luo, Y. Tse, and Y. Xie. 2020a. “The Market Quality of Commodity Futures Markets.” Journal of Futures Markets 40 (11): 1751–1766. doi:10.1002/fut.22115
  • Liu, Y., and A. Tsyvinski. 2021. “Risks and Returns of Cryptocurrency.” The Review of Financial Studies 34 (6): 2689–2727. doi:10.1093/rfs/hhaa113
  • Liu, R., S. Wan, Z. Zhang, and X. Zhao. 2020b. “Is the Introduction of Futures Responsible for the Crash of Bitcoin?” Finance Research Letters 34: 101259. doi:10.1016/j.frl.2019.08.007
  • Lo, A. W. 1991. “Long-term Memory in Stock Market Prices.” Econometrica 59: 1279–1313. doi:10.2307/2938368
  • Lo, A. 2004. “The Adaptive Markets Hypothesis.” The Journal of Portfolio Management 30 (5): 15–29. doi:10.3905/jpm.2004.442611
  • Lo, A. W., and A. C. MacKinlay. 1988. “Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test.” Review of Financial Studies 1 (1): 41–66. doi:10.1093/rfs/1.1.41
  • Locke, T. 2021. “Jamie Dimon Says Bitcoin is ‘a Little Bit of Fool’s Gold.” CNBC, October 4. https://www.cnbc.com/2021/10/04/jpmorgan-chase-ceo-jamie-dimon-bitcoin-is-a-little-bit-of-fools-gold.html
  • Lucey, B. M., S. A. Vigne, L. Yarovaya, and Y. Wang. 2022. “The Cryptocurrency Uncertainty Index.” Finance Research Letters 45: 102147.
  • Makarov, I., and A. Schoar. 2020. “Trading and Arbitrage in Cryptocurrency Markets.” Journal of Financial Economics 135: 293–319. doi:10.1016/j.jfineco.2019.07.001
  • Manning, L. 2021. Coinbase IPO Exceeds all Expectations, Showing More Promise for Bitcoin. NASDAQ. https://www.nasdaq.com/articles/coinbase-ipo-exceeds-all-expectations-showing-more-promise-for-bitcoin-2021-04-19.
  • Meegan, A., S. Corbet, C. Larkin, and B. Lucey. 2021. “Does Cryptocurrency Pricing Response to Regulatory Intervention Depend on Underlying Blockchain Architecture?.” Journal of International Financial Markets, Institutions and Money 70: 101280. doi:10.1016/j.intfin.2020.101280
  • Molinares, F. F., V. A. Reisen, and F. Cribari-Neto. 2009. “Robust Estimation in Long-Memory Processes under Additive Outliers.” Journal of Statistical Planning and Inference 139: 2511–2525. doi:10.1016/j.jspi.2008.12.014
  • Nadarajah, S., and J. Chu. 2017. “On the Inefficiency of Bitcoin.” Economics Letters 150: 6–9. doi:10.1016/j.econlet.2016.10.033
  • Nelson, D. 2021. “Gensler reiterates support for futures-based bitcoin ETFs.” CoinDesk, September 30. https://www.coindesk.com/policy/2021/09/29/gensler-reiterates-support-for-futures-based-bitcoin-etfs/
  • Peters, E. E. 1996. Chaos and Order in the Capital Markets. 2nd ed. New York: John Wiley & Sons, Inc.
  • Pincus, S. M. 1991. “Approximate Entropy as a Measure of System Complexity.” Proceedings of the National Academy of Sciences 88 (6): 2297–2301. doi:10.1073/pnas.88.6.2297
  • Reisen, V. A., C. Lévy-Leduc, and M. Taqqu. 2017. “An M-estimator for the long-memory parameter.” Journal of Statistical Planning and Inference 187: 44–55. doi:10.1016/j.jspi.2017.02.008
  • Robinson, P. M. 1995. “Gaussian Semiparametric Estimation of Long Range Dependence.” The Annals of Statistics 23 (5): 1630–1661. doi:10.1214/aos/1176324317
  • Roll, R. 1984. “A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market.” The Journal of Finance 39 (4): 1127–1139. doi:10.1111/j.1540-6261.1984.tb03897.x
  • Rösch, D. M., A. Subrahmanyam, and M. A. Dijk. 2017. “The Dynamics of Market Efficiency.” The Review of Financial Studies 30 (4): 1151–1187. doi:10.1093/rfs/hhw085
  • Salcedo-Sanz, S., D. Casillas-Pérez, J. Del Ser, C. Casanova-Mateo, L. Cuadra, M. Piles, et al. 2022. “Persistence in Complex Systems.” Physics Reports 957: 1–73. doi:10.1016/j.physrep.2022.02.002
  • Samuelson, P. A. 1965. “Proof That Properly Anticipated Prices Fluctuate Randomly.” Industrial Management Review 6: 41–49. http://www.evidenceinvestor.co.uk/wp-content/uploads/2016/08/Proof-That-Properly-Anticipated-Prices-Fluctuate-Randomly-Paul-A.-Samuelson-1965.pdf.
  • Sapkota, N., and K. Grobys. 2021. “Asset Market Equilibria in Cryptocurrency Markets: Evidence from a Study of Privacy and non-Privacy Coins.” Journal of International Financial Markets, Institutions and Money 74: 101402. doi:10.1016/j.intfin.2021.101402
  • Sebastião, H., and P. Godinho. 2020. “Bitcoin Futures: An Effective Tool for Hedging Cryptocurrencies.” Finance Research Letters 33: 101230. doi:10.1016/j.frl.2019.07.003
  • SEC. 2021. Funds Trading in Bitcoin Futures – Investor Bulletin. Accessed July 17, 2021. https://www.sec.gov/oiea/investor-alerts-and-bulletins/ib_fundstrading.
  • Sensoy, A., and E. Hacihasanoglu. 2014. “Time-varying Long Range Dependence in Energy Futures Markets.” Energy Economics 46: 318–327. doi:10.1016/j.eneco.2014.09.023
  • Shi, S., and Y. Shi. 2021. “Bitcoin Futures: Trade it or ban it?” The European Journal of Finance 27 (4–5): 381–396. doi:10.1080/1351847X.2019.1647865
  • Shimotsu, K. 2010. “Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend.” Econometric Theory 26: 501–540. doi:10.1017/S0266466609100075
  • Shimotsu, K., and P. C. Phillips. 2005. “Exact Local Whittle Estimation Of Fractional Integration.” The Annals of Statistics 33 (4): 1890–1933. doi:10.1214/009053605000000309
  • Shynkevich, A. 2021. “Impact of Bitcoin Futures on the Informational Efficiency of Bitcoin Spot Market.” Journal of Futures Markets 41 (1): 115–134. doi:10.1002/fut.22164
  • Tiwari, A. K., R. K. Jana, D. Das, and D. Roubaud. 2018. “Informational Efficiency of Bitcoin—An Extension.” Economics Letters 163: 106–109. doi:10.1016/j.econlet.2017.12.006
  • Tornell, A., and C. Yuan. 2012. “Speculation and Hedging in the Currency Futures Markets: Are They Informative to the Spot Exchange Rates.” Journal of Futures Markets 32 (2): 122–151. doi:10.1002/fut.20511
  • Urquhart, A. 2016. “The Inefficiency of Bitcoin.” Economics Letters 148: 80–82. doi:10.1016/j.econlet.2016.09.019
  • Urquhart, A., and F. McGroarty. 2016. “Are Stock Markets Really Efficient? Evidence of the Adaptive Market Hypothesis.” International Review of Financial Analysis 47: 39–49. doi:10.1016/j.irfa.2016.06.011
  • Vidal-Tomás, D. 2022. “All the Frequencies Matter in the Bitcoin Market: An Efficiency Analysis.” Applied Economics Letters 29 (3): 212–218. doi:10.1080/13504851.2020.1861196
  • Wang, C. 2001. “Investor Sentiment and Return Predictability in Agricultural Futures Markets.” Journal of Futures Markets 21 (10): 929–952. doi:10.1002/fut.2003
  • Wang, C. 2003. “The Behavior and Performance of Major Types of Futures Traders.” Journal of Futures Markets 23: 1–31.
  • Wang, C. 2004. “Futures Trading Activity and Predictable Foreign Exchange Market Movements.” Journal of Banking and Finance 28: 1023–1041.
  • Wang, J., and X. Wang. 2021. “COVID-19 and Financial Market Efficiency: Evidence from an Entropy-Based Analysis.” Finance Research Letters 101888.
  • Wei, W. C. 2018. “Liquidity and Market Efficiency in Cryptocurrencies.” Economics Letters 168: 21–24. doi:10.1016/j.econlet.2018.04.003
  • WHO. 2022. Timeline: WHO's COVID-19 Response. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline#event-6.
  • Wu, J., K. Xu, X. Zheng, and J. Chen. 2021. “Fractional Cointegration in Bitcoin Spot and Futures Markets.” Journal of Futures Markets 41: 1478–1494. doi:10.1002/fut.22216
  • Yentes, J. M., N. Hunt, K. K. Schmid, J. P. Kaipust, D. McGrath, and N. Stergiou. 2012. “The Appropriate Use of Approximate Entropy and Sample Entropy with Short Data Sets.” Annals of Biomedical Engineering 41 (2): 349–365. doi:10.1007/s10439-012-0668-3
  • Young, J. 2020. “Institutional Frenzy: CME Becomes 2nd Biggest Bitcoin Futures Market.” Cointelegraph, October 23. https://cointelegraph.com/news/institutional-frenzy-cme-becomes-2nd-biggest-bitcoin-futures-market.
  • Zhao, X., W. Hou, J. An, X. Liu, and Y. Zhang. 2021. “Initial Coin Offerings: What Rights Do Investors Have?” The European Journal of Finance 27 (4–5): 305–320. doi:10.1080/1351847X.2020.1858130

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.