The Nexus between Russian Capital Market and Bitcoin Rouble Exchange Rate

Debesh Bhowmik

doi:10.46977/apjmt.2022v02i04.004

Authors

Debesh Bhowmik Lincoln University College,Wisma Lincoln, No. 12-18, Jalan SS 6/12, 47301 Petaling Jaya, Selangor Darul Ehsan, Malaysia.

DOI:

https://doi.org/10.46977/apjmt.2022v02i04.004

Keywords:

Bitcoin R ouble, Dollar R ouble, MOEX index, RTX index, RUONIA

Abstract

The paper endeavour to explore the nexus between Bitcoin Rouble exchange rate and the Russian capital market using cointegration and vector error correction analysis taking the capital market indicators namely US Dollar Rouble exchange rate, MOEX index, RTX index, Moscow exchange trade turn over and RUONIA of Russia using daily data from 1/11/2021 to 18/4/2022 as a consequence of post pandemic recovery and sets back from war between Russia and Ukraine. The paper found that the trend line of Bitcoin Rouble rate is cyclical with four phases whose Wavelet threshold signal curve is explosive oscillatory. There are no short run causalities from the indicators of capital market to the Bitcoin Rouble price but there is insignificant and converging cointegrating long run causalities from those indicators where the relation between Bitcoin Rouble and US Dollar Rouble rate and MOEX index are significantly negative and the relation with RTX index is significantly positive. It was evident that there is little significant influence of Bitcoin Rouble pricing on the Russian capital market in the long run.
Key words-Bitcoin Rouble exchange rate, Dollar Rouble exchange rate, MOEX index, RTX index, RUONIA of Russia, Moscow exchange trade turn over, wavelet threshold seasonality, Wavelet threshold signal curve, cointegration, short run causality, long run causality.

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References

Abraham, R., & Tao, Z. (2019). The Valuation of Cryptocurrencies in Single-Asset and Multiple-Asset Models. Theoretical Economics Letters, 9(4), 1093-1113. https://doi.org/10.4236/tel.2019.94071

Almansour, B. Y., & Arabyat, Y. A. (2017). Investment decision making among Gulf investors: behavioural finance perspective. International Journal of Management Studies, 24(1), 41-71.

Ankenbrand, T., Bieri, D., Cortivo, R., Hoehener, J., & Hardjono, T. (2020, June). Proposal for a comprehensive (Crypto) asset taxonomy. In 2020 Crypto Valley Conference on Blockchain Technology (CVCBT) (pp. 16-26). IEEE.

Bank of Russia. (n.d). Ruonia. https://cbr.ru/eng/hd_base/Ruonia/

Basu, S., Saha, T. R., & Maity, S. K. (2018). Implications of cryptocurrency: A new business proposition of today’s entrepreneurial horizon. International Journal on Recent Trends in Business and Tourism (IJRTBT), 2(3), 64-70.

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.

Bhowmik, D. (2017). Real Effective Exchange Rate of India: Patterns and Determinants. International Journal on Recent Trends in Business and Tourism (IJRTBT), 1(4), 15-23.

Bilen, C., & Huzurbazar, S. (2002). Wavelet-based detection of outliers in time series. Journal of Computational and Graphical Statistics, 11(2), 311-327.

Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?. Finance Research Letters, 20, 192-198. https://www.sciencedirect.com/science/article/abs/pii/S1544612316301817

Danielsson, J. (2018). Cryptocurrencies don’t make sense. VoxEU. https://voxeu.org/article/cryptocurrencies-dont-make-sense

Daubechies, I. (1992). Ten lectures on wavelets. Society for industrial and applied mathematics. https://jqichina.files.wordpress.com/2012/02/ten-lectures-of-waveletsefbc88e5b08fe6b3a2e58d81e8aeb2efbc891.pdf

Donoho, D. L., & Johnstone, I. M. (1998). Minimax estimation via wavelet shrinkage. The Annals of Statistics, 26(3), 879-921. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.184.5755&rep=rep1&type=pdf

Financial Stability Board. (10th October 2018). Crypto-Asset Markets: Potential Channels for Future Stability Implications. https://www.fsb.org/2018/10/crypto-asset-markets-potential-channels-for-future-financial-stability-implications/

Fx-rate. (n.d). Find the best currency exchange. https://fx-rate.net

Haryanto, S., Subroto, A., & Ulpah, M. (2020). Disposition effect and herding behavior in the cryptocurrency market. Journal of Industrial and Business Economics, 47(1), 115-132.

Henry, E., Murtadho, A. M., & Bhaumik, A. (2020). The Relationship Between the Exchange Rate Fluctuations and Economic Growth in Nigeria. International Journal of Management and Human Science (IJMHS), 4(4), 11-18.

International Monetary Fund. (2022a, April). World Economic Outlook-2022. https://www.imf.org/en/Publications/WEO

International Monetary Fund. (2022b, April). Global Financial Stability Report-2022. https://www.imf.org/en/Publications/GFSR

Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3

Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica: Journal of the Econometric Society, 1551-1580. https://doi.org/10.2307/2938278

Kirk, C. P., & Swain, S. D. (2018). Consumer psychological ownership of digital technology. In Psychological Ownership and Consumer Behavior (pp. 69-90). Springer, Cham. https://doi.org/10.1007/978-3-319-77158-8_5

Konowicz, D.R. (2018). The New Game: Cryptocurrency Challenges US Economic Sanctions. Naval War College, Newport United States. https://apps.dtic.mil/sti/pdfs/AD1062142.pdf

Li, Z., Wang, J., & Li, K. (2019). Digital assets Price forecast based on POW mining mechanism. Open Journal of Social Sciences, 7(2), 185-198. https://doi.org/10.4236/jss.2019.72016

MacKinnon, J. G., Haug, A. A., & Michelis, L. (1999). Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics, 14(5), 563-577.

Mahdavieh, R. (2019). Governments' Adoption of Native Cryptocurrency: A Case Study of Iran, Russia, and Venezuela. https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1532&context=honorstheses

Pascual, M.G. (13th March 2022). Cryptocurrency: A lifeline for Russian oligarchs? International. https://english.elpais.com/international/2022-03-13/cryptocurrency-a-lifeline-for-russian-oligarchs.html

Thomson Reuters. (2022). Cryptocurrency regulations by country. https://www.thomsonreuters.com/en-us/posts/wp-content/uploads/sites/20/2022/04/Cryptos-Report-Compendium-2022.pdf