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Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?

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  • Ghaemi Asl, Mahdi
  • Raheem, Ibrahim D.
  • Rashidi, Muhammad Mahdi

Abstract

This study examines the interactions between Bitcoin (BTC) and other major financial markets (forex, equity and bond, and industrial and precious metals). This interaction is viewed from the spectrum of spillover analysis, hedging, and portfolio analyses. Due to the high volatility and volatility clustering nature of most financial series, particularly BTC, we rely on a Multivariate Factor Stochastic Volatility (mvFSV) Model of Kastner et al. (2017). In order to capture the influence of extreme market conditions, we use a quantile-based mvFSV Model. Among other things, results confirm the importance of quantile analysis as results are sensitive to market conditions. For instance, currencies and industrial and precious metals are net transmitters of shocks at lower and middle quantiles, while these assets change their status to the net receiver of shocks at the upper quantile. Results of the total connectedness show that there is a high degree of interconnectedness among the assets, as the total connectedness index ranges between 86% and 100%. Besides, Islamic equities perform such as the most currencies and conventional assets in terms of the transmission of shocks and diversification benefits. The hedging potentials of Bitcoin over other assets were also examined, and results confirm that the hedging effectiveness is commodity-specific. Policy implications of these results are discussed.

Suggested Citation

  • Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    • Handle: RePEc:eee:jrpoli:v:86:y:2023:i:pa:s0301420723008978
    DOI: 10.1016/j.resourpol.2023.104186
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    1. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    2. Chatziantoniou, Ioannis & Gabauer, David, 2021. "EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 1-14.
    3. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    4. Rezitis, Anthony N. & Kastner, Gregor, 2021. "On the joint volatility dynamics in international dairy commodity markets," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 60(2), January.
    5. Salisu, Afees A. & Ndako, Umar B. & Vo, Xuan Vinh, 2023. "Oil price and the Bitcoin market," Resources Policy, Elsevier, vol. 82(C).
    6. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
    7. Gunawan, David & Kohn, Robert & Nott, David, 2021. "Variational Bayes approximation of factor stochastic volatility models," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1355-1375.
    8. Chatziantoniou, Ioannis & Gabauer, David & Stenfors, Alexis, 2021. "Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach," Economics Letters, Elsevier, vol. 204(C).
    9. Sitara Karim & Muhammad Abubakr Naeem & Nawazish Mirza & Jessica Paule-Vianez, 2022. "Quantifying the hedge and safe-haven properties of bond markets for cryptocurrency indices," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 23(2), pages 191-205, January.
    10. Kumar, Anoop S & Padakandla, Steven Raj, 2022. "Testing the safe-haven properties of gold and bitcoin in the backdrop of COVID-19: A wavelet quantile correlation approach," Finance Research Letters, Elsevier, vol. 47(PB).
    11. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    12. Syed Jawad Hussain Shahzad & Elie Bouri & Mobeen Ur Rehman & David Roubaud, 2022. "The hedge asset for BRICS stock markets: Bitcoin, gold or VIX," The World Economy, Wiley Blackwell, vol. 45(1), pages 292-316, January.
    13. Gabauer, David, 2021. "Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    14. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    15. Li, Dongxin & Hong, Yanran & Wang, Lu & Xu, Pengfei & Pan, Zhigang, 2022. "Extreme risk transmission among bitcoin and crude oil markets," Resources Policy, Elsevier, vol. 77(C).
    16. Qiao, Xingzhi & Zhu, Huiming & Tang, Yiding & Peng, Cheng, 2023. "Time-frequency extreme risk spillover network of cryptocurrency coins, DeFi tokens and NFTs," Finance Research Letters, Elsevier, vol. 51(C).
    17. Choi, Sangyup & Shin, Junhyeok, 2022. "Bitcoin: An inflation hedge but not a safe haven," Finance Research Letters, Elsevier, vol. 46(PB).
    18. Bouri, Elie & Molnár, Peter & Azzi, Georges & Roubaud, David & Hagfors, Lars Ivar, 2017. "On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?," Finance Research Letters, Elsevier, vol. 20(C), pages 192-198.
    19. Gregor Kastner & Florian Huber, 2020. "Sparse Bayesian vector autoregressions in huge dimensions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1142-1165, November.
    20. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Chi‐Chuan Lee & Matthew Ntow‐Gyamfi, 2023. "Quantile price convergence and spillover effects among Bitcoin, Fintech, and artificial intelligence stocks," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 187-205, March.
    21. Takuji Kinkyo, 2022. "Hedging capabilities of Bitcoin for Asian currencies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1769-1784, April.
    22. 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.
    23. Elie Bouri & Naji Jalkh & Peter Molnár & David Roubaud, 2017. "Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?," Applied Economics, Taylor & Francis Journals, vol. 49(50), pages 5063-5073, October.
    24. Salisu, Afees A. & Isah, Kazeem & Akanni, Lateef O., 2019. "Improving the predictability of stock returns with Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 857-867.
    25. Darjus Hosszejni & Gregor Kastner, 2019. "Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol," Papers 1906.12123, arXiv.org, revised Feb 2021.
    26. Pal, Debdatta & Mitra, Subrata K., 2019. "Hedging bitcoin with other financial assets," Finance Research Letters, Elsevier, vol. 30(C), pages 30-36.
    27. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    28. Abdulnasser Hatemi-J & Mohamed A. Hajji & Elie Bouri & Rangan Gupta, 2022. "The Benefits of Diversification Between Bitcoin, Bonds, Equities and the US Dollar: A Matter of Portfolio Construction," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 39(04), pages 1-11, August.
    29. Shi, Yongjing & Tiwari, Aviral Kumar & Gozgor, Giray & Lu, Zhou, 2020. "Correlations among cryptocurrencies: Evidence from multivariate factor stochastic volatility model," Research in International Business and Finance, Elsevier, vol. 53(C).
    30. Imran Yousaf & Shoaib Ali & Elie Bouri & Tareq Saeed, 2022. "Information transmission and hedging effectiveness for the pairs crude oil-gold and crude oil-Bitcoin during the COVID-19 outbreak," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 1913-1934, December.
    31. Wang, Yizhi & Wei, Yu & Lucey, Brian M. & Su, Yang, 2023. "Return spillover analysis across central bank digital currency attention and cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    32. Wen, Fenghua & Tong, Xi & Ren, Xiaohang, 2022. "Gold or Bitcoin, which is the safe haven during the COVID-19 pandemic?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    33. Smales, L.A., 2019. "Bitcoin as a safe haven: Is it even worth considering?," Finance Research Letters, Elsevier, vol. 30(C), pages 385-393.
    34. Ahmed Jeribi & Mohamed Fakhfekh & Anis Jarboui, 2022. "Volatility dynamics and diversification benefits of Bitcoin under asymmetric and long memory effects," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 26(1), pages 65-83.
    35. Ross, Stephen A, 1989. "Information and Volatility: The No-Arbitrage Martingale Approach to Timing and Resolution Irrelevancy," Journal of Finance, American Finance Association, vol. 44(1), pages 1-17, March.
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    More about this item

    Keywords

    Bitcoin; Forex; Metals; Equity; Bonds; Stochastic volatility;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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