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Seoul Journal of Economics
[ Article ]
Seoul Journal of Economics - Vol. 36, No. 2, pp.233-246
ISSN: 1225-0279 (Print)
Print publication date 31 May 2023
Received 20 Feb 2023 Revised 22 May 2023 Accepted 23 May 2023
DOI: https://doi.org/10.22904/sje.2023.36.2.004

A Local Premium and Fluctuations: An Empirical Study on KorBit and the International Market

Jae-Young Kim ; Joon-Hyuck Lee
Jae-Young Kim, Corresponding Author, Department of Economics, Seoul National University jykim017@snu.ac.kr
Joon-Hyuck Lee, Department of Economics, Seoul National University jhlof97@snu.ac.kr

JEL Classification: C32; C58; G15

Abstract

Bitcoin, the first cryptocurrency created by Satoshi Nakamoto in 2009, has attracted considerable attention. The price of Bitcoin rose from $500 in the year 2014 to $70,000 in 2021, an astonishing 14,000% increase in the value, showing that it is a highly speculative asset. The Korean virtual currency exchange, KorBit, has emerged as a significant player in the global Bitcoin market, gaining considerable attention with a nontrivial premium known as the “kimchi premium”. We investigate how the Bitcoin’s value fluctuates and co-fluctuates across two markets of KorBit and international Bitcoin market (IntBit) based on a multivariate GARCH. We also explore what factors drive a relatively high yield and fluctuations in KorBit over IntBit. We have found that when the volatilities of Bitcoin’s yields in the two markets are contemporaneously high with a premium in KorBit, the correlation of the yields between the two markets decreases and highly fluctuates. We have also found that a relatively high yield of Bitcoin and its fluctuations in KorBit are mainly caused by depreciation of the Korean won and gains of KOSPI over S&P500.

Keywords:

Bitcoin, multivariate GARCH, kimchi premium

Acknowledgments

The authors thank Jae-Won Lee and two anonymous referees for helpful comments on the earlier version of this papar. This work was supported by the Research Grant, no. 0405-20190001, of the Center for National Competitiveness at the Institute of Economic Research Seoul National University.

References

  • Bauwens, L., Laurent, S., and Rombouts, J. V. “Multivariate GARCH Models: a Survey.” Journal of applied econometrics 21(No. 1 2006): 79-109. [https://doi.org/10.1002/jae.842]
  • Bera, A. K. and Higgins M. L. “ARCH models: properties, estimation and testing.” Journal of Economic Surveys 7(No. 4 1993): 305-366. [https://doi.org/10.1111/j.1467-6419.1993.tb00170.x]
  • Bergstra, J. A., de Leeuw, K. Bitcoin and Beyond: Exclusively Informational Monies. arXiv preprint arXiv: 1304.4758, 2013 .
  • Bollerslev, T. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics 31(No. 3 1986): 307-327. [https://doi.org/10.1016/0304-4076(86)90063-1]
  • Bollerslev, T. A Multivariate Generalized ARCH Model with Constant Conditional Correlations f or a Set o f Exchange Rates. Northwestern University, manuscript:1988.
  • Bollerslev, T., Chou, R. Y., and Kroner K. F. “ARCH modeling in finance: a review of the theory and empirical evidence.” Journal of Econometrics 52(No. 1-2 1992): 5-59. [https://doi.org/10.1016/0304-4076(92)90064-X]
  • Bollerslev T., Engle R., and Nelson, D. ARCH models. In Handbook of Econometrics, Engle R, McFadden D (eds). North Holland Press: Amsterdam, 1994.
  • Brandvold, M., Molnár, P., Vagstad, K., Valstad, O. C. A. “Price discovery on Bitcoin exchanges.” Journal of International Financial Markets, Institutions and Money 36(2015): 18-35. [https://doi.org/10.1016/j.intfin.2015.02.010]
  • Choi, K., Lehar, A., and Stauffer, R. Bitcoin Microstructure and the Kimchi Premium. Available at SSRN, 2020: https://ssrn.com/ abstract=3189051 or http://dx.doi.org/10.2139/ssrn.3189051 [https://doi.org/10.2139/ssrn.3189051]
  • Chu, J., Chan S., Nadarajah S., and Osterrieder J. “GARCH Modelling of Cryptocurrencies.” Journal of Risk and Financial Management 10(No. 4 2017): 1-15. [https://doi.org/10.3390/jrfm10040017]
  • Ciaian, P., Rajcaniova, M., d’Artis Kancs. “The economics of Bitcoin Price information.” Applied Economics 48(No. 19 2016): 1799-1815. [https://doi.org/10.1080/00036846.2015.1109038]
  • Engle, R. F. “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation.” Econometrica 50(1982): 987-1007. [https://doi.org/10.2307/1912773]
  • Garcia, D., and Schweitzer, F. “Social signals and algorithmic trading of Bitcoin.” Royal Society open science 2(No. 9 2015): 150288. [https://doi.org/10.1098/rsos.150288]
  • Gyamerah S.A. “Samuel Asante. Modelling the volatility of Bitcoin returns using GARCH models.” Quantitative Finance and Economics 3(No. 4 2019): 739-753. [https://doi.org/10.3934/QFE.2019.4.739]
  • Huh, I. “The Relationship between Bitcoin Volatility and the Traditional Financial Market.” Journal of Market Economy 48(No. 2 2019): 53-87. (In Korean) [https://doi.org/10.38162/JOME.48.2.3]
  • Huhtinen T. P. Bitcoin as a monetary system: Examining attention and attendance. Master’s thesis, Department of Finance, Aalto University School of Business, 2014.
  • Jung Yong-Gook. “A Study on the Nonlinearity in the Arbitrage Transaction-varying cointegration approaches of Cryptocurrency.” Review of International Money and Finance 9(No. 1 2019): 107-141. (In Korean) [https://doi.org/10.34251/ifadoi.9.1.201905.004]
  • Katsiampa P. “Volatility estimation for Bitcoin: A comparison of GARCH models.” Economics Letters 158(2017): 3-6. [https://doi.org/10.1016/j.econlet.2017.06.023]
  • Kim, D., Kim, Y., and Park, K. 암호자산 시장에서 국내외 가격차 발생 배경 및 시사점. 한국은행 BOK 이슈노트 제2018-8호, 2018.
  • Kim, J. Y., and Park, W. Y. “Some Empirical Evidence on Models of Fisher Relation.” Seoul Journal of Economics 31(No. 2 2018): 145-155.
  • Kristoufek, L. “What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis.” Plos One 10(No. 4 2015): e0123923 . [https://doi.org/10.1371/journal.pone.0123923]
  • Kroeger, A. and Sarkar, A. The Law of One Bitcoin Price? Federal Reserve Bank of Philadelphia, 2017.
  • Lee Y., and Rhee, J. H. “A VECM analysis of Bitcoin price using timevarying cointegration approach.” Journal of Derivatives and Quantitative Studies 30(No. 3 2022): 197-218. [https://doi.org/10.1108/JDQS-01-2022-0001]
  • Makarov I. and Schoar, A. “Trading and arbitrage in cryptocurrency markets.” Journal of Financial Economics 135(No. 2 2020): 293-319. [https://doi.org/10.1016/j.jfineco.2019.07.001]
  • Pagan, A. “The econometrics of financial markets.” Journal of Empirical Finance 3(No. 1996): 15-102. Palm FC. GARCH models of volatility. In Handbook of Statistics, Maddala GS, Rao CR (eds). [https://doi.org/10.1016/0927-5398(95)00020-8]
  • Shephard, N. Statistical aspects of ARCH and stochastic volatility. In Time Series Models in Econometrics, Finance and Other Fields, Hinkley DV, Cox DR, Barndorff-Nielsen OE (eds). Chapman & Hall: London, 1996.
  • Woo D., Gordon, I., and Laralov, V. Bitcoin: a first assessment. FX and Rates. December, Bank of America Merrill Lynch, 2013.