IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v153y2021ip1s0960077921009309.html
   My bibliography  Save this article

Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis

Author

Listed:
  • Ruan, Qingsong
  • Meng, Lu
  • Lv, Dayong

Abstract

This paper investigates the effect of introducing Bitcoin futures on Bitcoin spot market efficiency from the perspective of multifractality. We show that, after the introduction of Bitcoin futures, the fractal characteristics of Bitcoin spot market are weakened, suggesting that introducing Bitcoin futures help enhance market efficiency of Bitcoin spot market. We further use MF-X-DMA analysis and nonlinear Granger causality test to identify the source of increased spot-market efficiency. Results show that the cross-correlation between Bitcoin spot and futures returns is statistically significantly positive, and that the Bitcoin futures market and spot market has a two-way nonlinear Granger causality. Our results provide evidence that the price discovery in Bitcoin futures market help improve price efficiency of Bitcoin spot market efficiency.

Suggested Citation

  • Ruan, Qingsong & Meng, Lu & Lv, Dayong, 2021. "Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    • Handle: RePEc:eee:chsofr:v:153:y:2021:i:p1:s0960077921009309
    DOI: 10.1016/j.chaos.2021.111576
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921009309
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.111576?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Grossman, Sanford J, 1976. "On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information," Journal of Finance, American Finance Association, vol. 31(2), pages 573-585, May.
    2. Li, Jianfeng & Lu, Xinsheng & Qu, Ling, 2019. "Effectiveness of the RMB exchange rate regime reform: A new perspective from MF-DMA and MF-X-DMA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    3. Gennotte, Gerard & Leland, Hayne, 1990. "Market Liquidity, Hedging, and Crashes," American Economic Review, American Economic Association, vol. 80(5), pages 999-1021, December.
    4. Lu, Xinsheng & Tian, Jie & Zhou, Ying & Li, Zhihui, 2013. "Multifractal detrended fluctuation analysis of the Chinese stock index futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1452-1458.
    5. Lahmiri, Salim & Bekiros, Stelios & Bezzina, Frank, 2020. "Multi-fluctuation nonlinear patterns of European financial markets based on adaptive filtering with application to family business, green, Islamic, common stocks, and comparison with Bitcoin, NASDAQ, ," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    6. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    7. Stavroyiannis, Stavros & Babalos, Vassilios & Bekiros, Stelios & Lahmiri, Salim & Uddin, Gazi Salah, 2019. "The high frequency multifractal properties of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 62-71.
    8. Dirk G. Baur & Thomas Dimpfl, 2019. "Price discovery in bitcoin spot or futures?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 803-817, July.
    9. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    10. Mensi, Walid & Tiwari, Aviral Kumar & Yoon, Seong-Min, 2017. "Global financial crisis and weak-form efficiency of Islamic sectoral stock markets: An MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 135-146.
    11. Wang, Feng & Ye, Xin & Chen, HongTao & Wu, Congxin, 2021. "A portfolio strategy of stock market based on mean-MF-X-DMA model," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    12. Jacklin, Charles J & Kleidon, Allan W & Pfleiderer, Paul, 1992. "Underestimation of Portfolio Insurance and the Crash of October 1987," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 35-63.
    13. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    14. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    15. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    16. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    17. Akyildirim, Erdinc & Corbet, Shaen & Katsiampa, Paraskevi & Kellard, Neil & Sensoy, Ahmet, 2020. "The development of Bitcoin futures: Exploring the interactions between cryptocurrency derivatives," Finance Research Letters, Elsevier, vol. 34(C).
    18. Alexander, Carol & Heck, Daniel F., 2020. "Price discovery in Bitcoin: The impact of unregulated markets," Journal of Financial Stability, Elsevier, vol. 50(C).
    19. Zhu, Huijian & Zhang, Weiguo, 2018. "Multifractal property of Chinese stock market in the CSI 800 index based on MF-DFA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 497-503.
    20. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Does the introduction of futures improve the efficiency of Bitcoin?," Finance Research Letters, Elsevier, vol. 30(C), pages 367-370.
    21. Kapar, Burcu & Olmo, Jose, 2019. "An analysis of price discovery between Bitcoin futures and spot markets," Economics Letters, Elsevier, vol. 174(C), pages 62-64.
    22. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    23. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    24. Brauneis, Alexander & Mestel, Roland, 2018. "Price discovery of cryptocurrencies: Bitcoin and beyond," Economics Letters, Elsevier, vol. 165(C), pages 58-61.
    25. Jin, Jingyu & Yu, Jiang & Hu, Yang & Shang, Yue, 2019. "Which one is more informative in determining price movements of hedging assets? Evidence from Bitcoin, gold and crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    26. Hiemstra Craig & Kramer Charles, 1997. "Nonlinearity and Endogeneity in Macro-Asset Pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 2(3), pages 1-18, October.
    27. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    28. Qin, Jing & Lu, Xinsheng & Zhou, Ying & Qu, Ling, 2015. "The effectiveness of China’s RMB exchange rate reforms: An insight from multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 443-454.
    29. Cao, H Henry, 1999. "The Effect of Derivative Assets on Information Acquisition and Price Behavior in a Rational Expectations Equilibrium," The Review of Financial Studies, Society for Financial Studies, vol. 12(1), pages 131-163.
    30. Gao-Feng Gu & Wei-Xing Zhou, 2010. "Detrending moving average algorithm for multifractals," Papers 1005.0877, arXiv.org, revised Jun 2010.
    31. Fassas, Athanasios P. & Papadamou, Stephanos & Koulis, Alexandros, 2020. "Price discovery in bitcoin futures," Research in International Business and Finance, Elsevier, vol. 52(C).
    32. Danthine, Jean-Pierre, 1978. "Information, futures prices, and stabilizing speculation," Journal of Economic Theory, Elsevier, vol. 17(1), pages 79-98, February.
    33. Zhi-Qiang Jiang & Wei-Xing Zhou, 2011. "Multifractal detrending moving average cross-correlation analysis," Papers 1103.2577, arXiv.org, revised Mar 2011.
    34. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
    35. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    36. Zunino, L. & Tabak, B.M. & Figliola, A. & Pérez, D.G. & Garavaglia, M. & Rosso, O.A., 2008. "A multifractal approach for stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6558-6566.
    37. 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).
    38. Bai, Man-Ying & Zhu, Hai-Bo, 2010. "Power law and multiscaling properties of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1883-1890.
    39. Ekkehart Boehmer & Eric K. Kelley, 2009. "Institutional Investors and the Informational Efficiency of Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3563-3594, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Zixiu & Fantazzini, Dean, 2022. "Using crypto assets pricing methods to build technical oscillators for short-term bitcoin trading," MPRA Paper 115508, University Library of Munich, Germany.
    2. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    3. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ruan, Qingsong & Zhou, Mi & Yin, Linsen & Lv, Dayong, 2021. "Hedging effectiveness of Chinese Treasury bond futures: New evidence based on nonlinear analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Zhou, Yaping & Lu, Baoqun & Lv, Dayong & Ruan, Qingsong, 2019. "The informativeness of options-trading activities: Non-linear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    3. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    4. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.
    5. Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
    6. Ruan, Qingsong & Yang, Haiquan & Lv, Dayong & Zhang, Shuhua, 2018. "Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 243-256.
    7. Ghazani, Majid Mirzaee & Khosravi, Reza, 2020. "Multifractal detrended cross-correlation analysis on benchmark cryptocurrencies and crude oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    8. Efe Caglar Cagli & Pinar Evrim Mandaci, 2021. "Information transmission between bitcoin derivatives and spot markets: high-frequency causality analysis with Fourier approximation," Economics and Business Letters, Oviedo University Press, vol. 10(4), pages 394-402.
    9. Ruan, Qingsong & Bao, Junjie & Zhang, Manqian & Fan, Limin, 2019. "The effects of exchange rate regime reform on RMB markets: A new perspective based on MF-DCCA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 122-134.
    10. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    11. Shao, Wei & Wang, Jian, 2020. "Does the “ice-breaking” of South and North Korea affect the South Korean financial market?," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    12. Prashant Sharma & Prashant Gupta & Dinesh Kumar Sharma & Gaurav Agarwal, 2022. "Investigating the Efficiency of Bitcoin Futures in Price Discovery," International Journal of Economics and Financial Issues, Econjournals, vol. 12(3), pages 104-109, May.
    13. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    14. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    15. Zhou, Weijie & Dang, Yaoguo & Gu, Rongbao, 2013. "Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1429-1438.
    16. Stošić, Dusan & Stošić, Darko & Stošić, Tatijana & Eugene Stanley, H., 2015. "Multifractal properties of price change and volume change of stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 46-51.
    17. Ruan, Qingsong & Jiang, Wei & Ma, Guofeng, 2016. "Cross-correlations between price and volume in Chinese gold markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 10-22.
    18. Apostolakis, George N., 2024. "Bitcoin price volatility transmission between spot and futures markets," International Review of Financial Analysis, Elsevier, vol. 94(C).
    19. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    20. Chan, Stephen & Chu, Jeffrey & Zhang, Yuanyuan & Nadarajah, Saralees, 2022. "An extreme value analysis of the tail relationships between returns and volumes for high frequency cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:153:y:2021:i:p1:s0960077921009309. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.