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Giver and the receiver: Understanding spillover effects and predictive power in cross-market Bitcoin prices

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  • Gillaizeau, Marc
  • Jayasekera, Ranadeva
  • Maaitah, Ahmad
  • Mishra, Tapas
  • Parhi, Mamata
  • Volokitina, Evgeniia

Abstract

We identify and characterise the ‘givers and the receivers’ of volatility in cross-market Bitcoin prices and discuss international diversification strategies in this context. Using both time and frequency domain mechanisms, we provide estimates of outward and inward spillover effects. These have implications for (weak-form) cross-market inefficiency. In our setting, we treat high-degree of spillover as an indicator of weak-form inefficiency because investors can utilise information on the dynamic spillover effects to produce a best long-run prediction of the market. Our results show that Bitcoin prices depict strong (dynamic) spillover in volatility, especially during episodes of high uncertainty. The Bitcoin-USD exchange rate possesses net predictive power, mirrored by the tendency of the Bitcoin-EURO market as a net receiver relative to other markets. Robustness exercise generally supports our claim. The overall implication is that during episodes of high uncertainty, Bitcoin markets depict greater dynamic inefficiency, instrumenting the role of asymmetric information in the path-dependence and predictive power of Bitcoin prices in an interdependent market.

Suggested Citation

  • Gillaizeau, Marc & Jayasekera, Ranadeva & Maaitah, Ahmad & Mishra, Tapas & Parhi, Mamata & Volokitina, Evgeniia, 2019. "Giver and the receiver: Understanding spillover effects and predictive power in cross-market Bitcoin prices," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 86-104.
    • Handle: RePEc:eee:finana:v:63:y:2019:i:c:p:86-104
    DOI: 10.1016/j.irfa.2019.03.005
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    as
    1. Cheah, Eng-Tuck & Mishra, Tapas & Parhi, Mamata & Zhang, Zhuang, 2018. "Long Memory Interdependency and Inefficiency in Bitcoin Markets," Economics Letters, Elsevier, vol. 167(C), pages 18-25.
    2. Wiggins, James B, 1991. "Empirical Tests of the Bias and Efficiency of the Extreme-Value Variance Estimator for Common Stocks," The Journal of Business, University of Chicago Press, vol. 64(3), pages 417-432, July.
    3. Alvarez-Ramirez, J. & Rodriguez, E. & Ibarra-Valdez, C., 2018. "Long-range correlations and asymmetry in the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 948-955.
    4. Caporale, Guglielmo Maria & Gil-Alana, Luis & Plastun, Alex, 2018. "Persistence in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 46(C), pages 141-148.
    5. Brian M. Lucey & Charles Larkin & Fergal O'Connor, 2014. "Gold markets around the world - who spills over what, to whom, when?," Applied Economics Letters, Taylor & Francis Journals, vol. 21(13), pages 887-892, September.
    6. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    7. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    8. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    9. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    10. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    11. Fernández-Rodríguez, Fernando & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2016. "Using connectedness analysis to assess financial stress transmission in EMU sovereign bond market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 126-145.
    12. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    13. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    14. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    15. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Volatility spillovers across stock index futures in Asian markets: Evidence from range volatility estimators," Finance Research Letters, Elsevier, vol. 17(C), pages 158-166.
    16. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    17. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    18. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    19. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    20. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    21. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
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    Cited by:

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    2. Luo, Di & Mishra, Tapas & Yarovaya, Larisa & Zhang, Zhuang, 2021. "Investing during a Fintech Revolution: Ambiguity and return risk in cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    3. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    4. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    5. Wang, Jinghua & Ngene, Geoffrey M., 2020. "Does Bitcoin still own the dominant power? An intraday analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Arfaoui, Nadia & Naeem, Muhammad Abubakr & Boubaker, Sabri & Mirza, Nawazish & Karim, Sitara, 2023. "Interdependence of clean energy and green markets with cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    7. Tobias Burggraf, 2020. "Bitcoin and Global Political Uncertainty – Evidence from the U.S. Election Cycle," Economics Bulletin, AccessEcon, vol. 40(1), pages 727-742.
    8. Nikolaos A. Kyriazis, 2019. "A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets," JRFM, MDPI, vol. 12(4), pages 1-17, November.
    9. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    10. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    11. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-04250269, HAL.
    12. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    13. Sofiane Aboura, 2022. "A note on the Bitcoin and Fed Funds rate," Empirical Economics, Springer, vol. 63(5), pages 2577-2603, November.
    14. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    15. Tiantian Liu & Tadahiro Nakajima & Shigeyuki Hamori, 2022. "The impact of economic uncertainty caused by COVID-19 on renewable energy stocks," Empirical Economics, Springer, vol. 62(4), pages 1495-1515, April.
    16. Jiang, Wen & Xu, Qiuhua & Zhang, Ruige, 2022. "Tail-event driven network of cryptocurrencies and conventional assets," Finance Research Letters, Elsevier, vol. 46(PB).
    17. Huang, Yingying & Duan, Kun & Mishra, Tapas, 2021. "Is Bitcoin really more than a diversifier? A pre- and post-COVID-19 analysis," Finance Research Letters, Elsevier, vol. 43(C).
    18. Nikolaos A. Kyriazis, 2021. "Investigating the diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 845-861, December.
    19. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    20. Zhou, Mei-Jing & Huang, Jian-Bai & Chen, Jin-Yu, 2022. "Time and frequency spillovers between political risk and the stock returns of China's rare earths," Resources Policy, Elsevier, vol. 75(C).
    21. Stelios Bekiros & Axel Hedström & Evgeniia Jayasekera & Tapas Mishra & Gazi Salah Uddin, 2021. "Correlated at the Tail: Implications of Asymmetric Tail-Dependence Across Bitcoin Markets," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1289-1299, December.

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    More about this item

    Keywords

    Cross-market Bitcoin prices; Return and volatility spillovers; Uncertainty; Inefficiency; Prediction;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium

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