Unveiling the linkages between emerging stock market indices and cryptocurrencies

Main Article Content

Wajid Shakeel Ahmed
Ahsan Mehmood
Talha Sheikh
Allah Bachaya


This paper investigated the relationship between cryptocurrencies and emerging stock market indices using fractional integration and co-integration technique. Particularly, fractional integration is applied to examine stochastic properties of individual assets and fractional cointegration to analyse bivariate connectedness. Our findings unveil the absence of mean reversion in majority cases which indicates high persistence in series. Furthermore, bivariate analysis reveals disconnection between cryptocurrencies prices and stock indices. Surprisingly, a different picture emerges on using conditional volatility instead of prices. Like, conditional volatility-based estimation uncovers evidence of mean reversion in univariate analysis as expected. There is some evidence of cointegration on volatility grounds between cryptocurrencies and emerging stock market indices. Our findings implies that investment decision regarding digital currencies should be taken cautiously. As cryptocurrencies are extremely volatile with high degree of persistence which can make them counterproductive.

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Unveiling the linkages between emerging stock market indices and cryptocurrencies. (2022). Asian Academy of Management Journal, 27(2), 189–209. https://doi.org/10.21315/aamj2022.27.2.9
Original Articles


Abakah, E. J. A., Gil-Alana, L. A., Madigu, G., & Romero-Rojo, F. (2020). Volatility persistence in cryptocurrency markets under structural breaks. International Review of Economics and Finance, 69, 680–691. https://doi.org/10.1016/j.iref.2020.06.035

Aftab, M., Ahmad, R., Ismail, I., & Phylaktis, K. (2021). Economic integration and the currency and equity markets nexus. International Journal of Finance & Economics, 26(4), 5278–5301. https://doi.org/10.1002/ijfe.2065

Arouri, M. E. H., & Foulquier, P. (2012). Financial market integration: Theory and empirical results. Economic Modelling, 29(2), 382–394. https://doi.org/10.1016/j.econmod.2011.11.009

Aslanidis, N., Bariviera, A. F., & Martínez-Ibañez, O. (2019). An analysis of cryptocurrencies conditional cross correlations. Finance Research Letters, 31, 130–137. https://doi.org/10.1016/j.frl.2019.04.019

Aysan, A. F., Demir, E., Gozgor, G., & Lau, C. K. M. (2019). Effects of the geopolitical risks on Bitcoin returns and volatility. Research in International Business and Finance, 47, 511–518. https://doi.org/10.1016/j.ribaf.2018.09.011

Ayub, U., Shah, S. Z. A., & Abbas, Q. (2015). Robust analysis for downside risk in portfolio management for a volatile stock market. Economic Modelling, 44, 86–96. https://doi.org/10.1016/j.econmod.2014.10.001

Baek, C., & Elbeck, M. (2015). Bitcoins as an investment or speculative vehicle? A first look. Applied Economics Letters, 22(1), 30–34. https://doi.org/10.1080/13504851.2014.916379

Bariviera, A. F. (2017). The inefficiency of Bitcoin revisited: A dynamic approach. Economics Letters, 161, 1–4. https://doi.org/10.1016/j.econlet.2017.09.013

Bartos, J. (2015). Does Bitcoin follow the hypothesis of efficient market? International Journal of Economic Sciences, 4(2), 10–23. https://doi.org/10.20472/ES.2015.4.2.002

Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189. https://doi.org/10.1016/j.intfin.2017.12.004

Baur, D. G., & Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217–229. https://doi.org/10.1111/j.1540-6288.2010.00244.x

Beran, J. (1994). Statistics for long-memory processes (Vol. 61). CRC Press.

Bouoiyour, J., & Selmi, R. (2015). Bitcoin price: Is it really that new round of volatility can be on way? In MPRA Paper (No. 65580; MPRA Paper, Issue 65580). University Library of Munich, Germany. https://ideas.repec.org/p/pra/mprapa/65580.html

Bouri, E., Azzi, G., & Haubo Dyhrberg, A. (2017). On the return-volatility relationship in the Bitcoin market around the price crash of 2013. Economics: The Open-Access, Open-Assessment E-Journal, 11(1), 1–16. https://doi.org/10.5018/economics-ejournal.ja.2017-2

Bouri, E., Gil?Alana, L. A., Gupta, R., & Roubaud, D. (2019). Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks. International Journal of Finance and Economics, 24(1), 412–426. https://doi.org/10.1002/ijfe.1670

Bouri, E., Gupta, R., Tiwari, A. K., & Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87–95. https://doi.org/10.1016/j.frl.2017.02.009

Bouri, E., Hussain Shahzad, S. J., & Roubaud, D. (2020). Cryptocurrencies as hedges and safe-havens for US equity sectors. The Quarterly Review of Economics and Finance, 75, 294–307. https://doi.org/10.1016/j.qref.2019.05.001

Bouri, E., Lucey, B., & Roubaud, D. (2020a). Cryptocurrencies and the downside risk in equity investments. Finance Research Letters, 33, 101211. https://doi.org/10.1016/j.frl.2019.06.009

Bouri, E., Lucey, B., & Roubaud, D. (2020b). The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages. Finance Research Letters, 33, 101188. https://doi.org/10.1016/j.frl.2019.05.006

Brière, M., Oosterlinck, K., & Szafarz, A. (2015). Virtual currency, tangible return: Portfolio diversification with bitcoin. Journal of Asset Management, 16(6), 365–373. https://doi.org/10.1057/jam.2015.5

Caporale, G. M., Gil-Alana, L., & Plastun, A. (2018). Persistence in the cryptocurrency market. Research in International Business and Finance, 46, 141–148. https://doi.org/10.1016/j.ribaf.2018.01.002

Caporale, G. M., & Plastun, A. (2019). The day of the week effect in the cryptocurrency market. Finance Research Letters, 31. https://doi.org/10.1016/j.frl.2018.11.012

Cerqueti, R., Giacalone, M., & Mattera, R. (2020). Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling. Information Sciences, 527, 1–26. https://doi.org/10.1016/j.ins.2020.03.075

Charfeddine, L., Benlagha, N., & Maouchi, Y. (2020). Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors. Economic Modelling, 85, 198–217. https://doi.org/10.1016/j.econmod.2019.05.016

Cheah, E. T., & Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics Letters, 130, 32–36. https://doi.org/10.1016/j.econlet.2015.02.029

Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). GARCH Modelling of Cryptocurrencies. Journal of Risk and Financial Management, 10(4), 17. https://doi.org/10.3390/jrfm10040017

Ciaian, P., Rajcaniova, M., & Kancs, d’Artis. (2016). The economics of BitCoin price formation. Applied Economics, 48(19), 1799–1815. https://doi.org/10.1080/00036846.2015.1109038

Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018a). Exploring the dynamic relationships between cryptocurrencies and other financial assets. Economics Letters, 165, 28–34. https://doi.org/10.1016/j.econlet.2018.01.004

Dahlhaus, R. (1989). Efficient parameter estimation for self-similar processes. Annals of Statistics, 17(4), 1749–1766. https://doi.org/10.1214/aos/1176347393

Dooley, M., & Hutchison, M. (2009). Transmission of the U.S. subprime crisis to emerging markets: Evidence on the decoupling–recoupling hypothesis. Journal of International Money and Finance, 28(8), 1331–1349. https://doi.org/10.1016/j.jimonfin.2009.08.004

Dyhrberg, A. H. (2016a). Bitcoin, gold and the dollar – A GARCH volatility analysis. Finance Research Letters, 16, 85–92. https://doi.org/10.1016/j.frl.2015.10.008

Dyhrberg, A. H. (2016b). Hedging capabilities of bitcoin. Is it the virtual gold? Finance Research Letters, 16, 139–144. https://doi.org/10.1016/j.frl.2015.10.025

Fakhfekh, M., & Jeribi, A. (2020). Volatility dynamics of crypto-currencies’ returns: Evidence from asymmetric and long memory GARCH models. Research in International Business and Finance, 51, 101075. https://doi.org/10.1016/j.ribaf.2019.101075

Fang, F., Ventre, C., Basios, M., Kong, H., Kanthan, L., Li, L., Martinez-Regoband, D., & Wu, F. (2020). Cryptocurrency trading: A comprehensive survey. ArXiv, ArXiv:2003 [q-Fin], 11352. https://doi.org/10.48550/arXiv.2003.11352

Gil-Alana, L. A., Abakah, E. J. A., & Rojo, M. F. R. (2020). Cryptocurrencies and stock market indices. Are they related? Research in International Business and Finance, 51, 101063. https://doi.org/10.1016/j.ribaf.2019.101063

Gil-Alana, L. A., & Hualde, J. (2009). Fractional integration and cointegration: An overview and an empirical application. In T. C. Mills & K. Patterson (Eds.), Palgrave Handbook of Econometrics: Volume 2: Applied Econometrics (434– 469). Palgrave Macmillan. https://doi.org/10.1057/9780230244405_10

Glaser, F., Zimmermann, K., Haferkorn, M., Weber, M. C., & Siering, M. (2014). Bitcoin - Asset or Currency? Revealing Users’ Hidden Intentions (SSRN Scholarly Paper ID 2425247). Social Science Research Network. https://papers.ssrn.com/abstract=2425247

Goodell, J. W., & Goutte, S. (2021). Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis. Finance Research Letters, 38, 101625. https://doi.org/10.1016/j.frl.2020.101625

Guesmi, K., Saadi, S., Abid, I., & Ftiti, Z. (2019). Portfolio diversification with virtual currency: Evidence from bitcoin. International Review of Financial Analysis, 63, 431–437. https://doi.org/10.1016/j.irfa.2018.03.004

Hafner, C. (2018). Testing for Bubbles in Cryptocurrencies with Time-Varying Volatility (SSRN Scholarly Paper ID 3105251). Social Science Research Network. https://doi.org/10.2139/ssrn.3105251

Halaburda, H., & Gandal, N. (2014). Competition in the cryptocurrency market. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2506463

Härdle, W. K., Harvey, C. R., & Reule, R. C. G. (2019). Understanding cryptocurrencies. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3360304

Hu, Y., Li, X., & Shen, D. (2020). Attention allocation and international stock return comovement: Evidence from the Bitcoin market. Research in International Business and Finance, 54, 101286. https://doi.org/10.1016/j.ribaf.2020.101286

Kajtazi, A., & Moro, A. (2019). The role of bitcoin in well diversified portfolios: A comparative global study. International Review of Financial Analysis, 61, 143–157. https://doi.org/10.1016/j.irfa.2018.10.003

Katsiampa, P. (2017). Volatility estimation for Bitcoin: A comparison of GARCH models. Economics Letters, 158, 3–6. https://doi.org/10.1016/j.econlet.2017.06.023

Kim, T. (2017). On the transaction cost of Bitcoin. Finance Research Letters, 23, 300–305. https://doi.org/10.1016/j.frl.2017.07.014

Klein, T., Pham Thu, H., & Walther, T. (2018). Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance. International Review of Financial Analysis, 59, 105–116. https://doi.org/10.1016/j.irfa.2018.07.010

Kristoufek, L. (2015). What are the main drivers of the bitcoin price? evidence from wavelet coherence analysis. PLOS ONE, 10(4), e0123923. https://doi.org/10.1371/journal.pone.0123923

Kurihara, Y., & Fukushima, A. (2017). The market efficiency of Bitcoin: A weekly anomaly perspective. Journal of Applied Finance & Banking, 7(3). https://econpapers.repec.org/article/sptapfiba/v_3a7_3ay_3a2017_3ai_3a3_3af_3a7_5f3_5f4.htm

Kurka, J. (2019). Do cryptocurrencies and traditional asset classes influence each other? Finance Research Letters, 31, 38–46. https://doi.org/10.1016/j.frl.2019.04.018

Liu, J., & Serletis, A. (2019). Volatility in the cryptocurrency market. Open Economies Review, 30(4), 779–811. https://doi.org/10.1007/s11079-019-09547-5

Liu, Y., & Tsyvinski, A. (2018). Risks and returns of cryptocurrency. https://doi.org/10.2139/ssrn.3226952

Narayan, S., Sriananthakumar, S., & Islam, S. Z. (2014). Stock market integration of emerging Asian economies: Patterns and causes. Economic Modelling, 39, 19–31. https://doi.org/10.1016/j.econmod.2014.02.012

Phillip, A., Chan, J. S. K., & Peiris, S. (2018). A new look at cryptocurrencies. Economics Letters, 163, 6–9. https://doi.org/10.1016/j.econlet.2017.11.020

Qureshi, S., Aftab, M., Bouri, E., & Saeed, T. (2020). Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency. Physica A: Statistical Mechanics and Its Applications, 559, 125077. https://doi.org/10.1016/j.physa.2020.125077

Shahzad, S. J. H., Bouri, E., Roubaud, D., Kristoufek, L., & Lucey, B. (2019). Is Bitcoin a better safe-haven investment than gold and commodities? International Review of Financial Analysis, 63, 322–330. https://doi.org/10.1016/j.irfa.2019.01.002

Symitsi, E., & Chalvatzis, K. J. (2018). Return, volatility and shock spillovers of Bitcoin with energy and technology companies. Economics Letters, 170, 127–130. https://doi.org/10.1016/j.econlet.2018.06.012

Tan, S. K., Chan, J. S. K., & Ng, K. H. (2020). On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure. Finance Research Letters, 32, 101075. https://doi.org/10.1016/j.frl.2018.12.023

Tran, V. L., & Leirvik, T. (2019). Efficiency in the markets of crypto-currencies. Finance Research Letters, 35, 101382. https://doi.org/10.1016/j.frl.2019.101382

Urquhart, A. (2016). The inefficiency of Bitcoin. Economics Letters, 148, 80–82. https://doi.org/10.1016/j.econlet.2016.09.019

Urquhart, A. (2017). Price clustering in Bitcoin. Economics Letters, 159, 145–148. https://doi.org/10.1016/j.econlet.2017.07.035

Yi, S., Xu, Z., & Wang, G. J. (2018). Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency? International Review of Financial Analysis, 60, 98–114. https://doi.org/10.1016/j.irfa.2018.08.012

Zhang, Y. J., Bouri, E., Gupta, R., & Ma, S. J. (2021). Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach. The North American Journal of Economics and Finance, 55, 101296. https://doi.org/10.1016/j.najef.2020.101296