Connectedness Analysis And Investment Strategy Between Stablecoins And International Stock Indices

Ika Maradjabessy; Zaafri Ananto Husodo

doi:10.24912/jm.v28i3.2008

Authors

Ika Maradjabessy Program Pascasarjana Ilmu Manajemen, Economi dan Bisnis, Universitas Indonesia, Depok
Zaafri Ananto Husodo Program Pascasarjana Ilmu Manajemen, Economi dan Bisnis, Universitas Indonesia, Depok

DOI:

https://doi.org/10.24912/jm.v28i3.2008

Keywords: Stablecoin; Stocks Indices; DCC-GARCH; T-copula DCC-GARCH.

Abstract

This research analyzes the dynamic connectedness between fiat-based stablecoins represented by USDC, USDP, and USDT, and gold-based stablecoins represented by DGX and GLC with indices international stocks represented by S&P500, STOXX50, Nikkei225, CSI300, and JKSE using the new method, the DCC-GARCH based dynamic, connected approach. The result shows dynamic connectedness between stablecoins and the stocks indices; this research continues to adopt the DCC-GARCH t-copula method to find investment strategies by calculating the hedging ratio and portfolio weight. Overall, this research finds evidence that portfolio construction can significantly reduce investment risk in all assets used on two assets, Nikkei225 and JKSE. In contrast, the investment strategy with portfolio weights in long positions is suitable for gold-based stablecoins GLC and DGX, where these two assets can be a diversification strategy in compiling a portfolio in long positions with all the assets used.

Author Biographies

Ika Maradjabessy, Program Pascasarjana Ilmu Manajemen, Economi dan Bisnis, Universitas Indonesia, Depok

ika.maradjabessy@ui.ac.id

Zaafri Ananto Husodo, Program Pascasarjana Ilmu Manajemen, Economi dan Bisnis, Universitas Indonesia, Depok

z.husodo@ui.ac.id

References

Ante, L., Fiedler, I., & Strehle, E. (2021). The Influence Of Stablecoin Issuances On Cryptocurrency Markets. Finance Research Letters, 41(June 2020), 101867. https://doi.org/10.1016/j.frl.2020.101867.

Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil And Asset Classes Implied Volatilities: Investment Strategies And Hedging Effectiveness. Energy Economics, 91, 104762. https://doi.org/10.1016/j.eneco.2020.104762.

Aslam, F., Aziz, S., Nguyen, D. K., Mughal, K. S., & Khan, M. (2020). On The Efficiency Of Foreign Exchange Markets In Times Of The COVID-19 Pandemic. Technological Forecasting and Social Change, 161(August), 120261. https://doi.org/10.1016/j.techfore.2020.120261.

Balcilar, M., Ozdemir, H., & Agan, B. (2022). Effects Of COVID-19 On Cryptocurrency And Emerging Market Connectedness: Empirical Evidence From Quantile, Frequency, And Lasso Networks. Physica A: Statistical Mechanics and Its Applications, 604, 127885. https://doi.org/10.1016/j.physa.2022.127885.

Banerjee, A. K., Akhtaruzzaman, M., Dionisio, A., Almeida, D., & Sensoy, A. (2022). Nonlinear Nexus Between Cryptocurrency Returns And COVID-19 News Sentiment. Journal of Behavioral and Experimental Finance, 36, 100747. https://doi.org/10.1016/j.jbef.2022.100747.

Baur, D. G., & Hoang, L. T. (2021). A Crypto Safe Haven Against Bitcoin. Finance Research Letters, 38. https://doi.org/10.1016/j.frl.2020.101431.

Bilgin, M., & Yilmaz, K. (2018). Producer Price Inflation Connectedness And Input-Output Networks. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3244645.

Bollerslev, T. (1990). Modelling The Coherence In Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model. The Review of Economics and Statistics, 72(3), 498. https://doi.org/10.2307/2109358.

Bouri, E., Gabauer, D., Gupta, R., & Tiwari, A. K. (2021). Volatility Connectedness Of Major Cryptocurrencies: The Role Of Investor Happiness. Journal of Behavioral and Experimental Finance, 30, 100463. https://doi.org/10.1016/j.jbef.2021.100463.

Brown, M. B., & Forsythe, A. B. (1974). Robust Tests For The Equality Of Variances. Journal of the American Statistical Association, 69(346), 364–367. https://doi.org/10.1080/ 01621459.1974.10482955.

Chan, W. H., Le, M., & Wu, Y. W. (2019). Holding Bitcoin Longer: The Dynamic Hedging Abilities Of Bitcoin. Quarterly Review of Economics and Finance, 71, 107–113. https://doi.org/10.1016/j.qref.2018.07.004.

Chohan, U. W. (2019). Are Stable Coins Stable? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3326823.

Diebold, F. X., & Yilmaz, K. (2012). Better To Give Than To Receive: Predictive Directional Measurement Of Volatility Spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006.

Diebold, F. X., & Yilmaz, K. (2014). On The Network Topology Of Variance Decompositions: Measuring The Connectedness Of Financial Firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012.

Ederington, L. H. (1979). The Hedging Performance Of The New Futures Markets. The Journal of Finance, 34(1), 157–170. https://doi.org/10.1111/j.1540-6261.1979.tb02077.x

Engle, RF., Sheppard, K. (2001). Dcc Mv-Garch. Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate Garch, NBER Working Paper Series, 8554. https://doi.org/10.3386/w8554.

Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class Of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics, 20(3). https://doi.org/10.1198/073500102288618487.

Gabauer, D. (2020). Volatility Impulse Response Analysis For DCC-GARCH Models: The Role Of Volatility Transmission Mechanisms. Journal of Forecasting. https://doi.org/ 10.1002/for.2648.

Gao, H. L., & Mei, D. C. (2019). The Correlation Structure In The International Stock Markets During The Global Financial Crisis. Physica A: Statistical Mechanics and Its Applications, 534, 122056. https://doi.org/10.1016/j.physa.2019.122056.

Garcia-Jorcano, L., & Benito, S. (2020). Studying The Properties Of The Bitcoin As A Diversifying And Hedging Asset Through A Copula Analysis: Constant And Time-Varying. Research in International Business and Finance, 54. https://doi.org/10.1016/j.ribaf.2020.101300.

Hou, Y., Li, S., & Wen, F. (2019). Time-Varying Volatility Spillover Between Chinese Fuel Oil And Stock Index Futures Markets Based On A DCC-GARCH Model With A Semi-Nonparametric Approach. Energy Economics, 83, 119–143. https://doi.org/10.1016/j.eneco.2019.06.020.

Ito, K., Mita, M., Ohsawa, S., & Tanaka, H. (2020). What Is Stablecoin?: A Survey On Its Mechanism And Potential As Decentralized Payment Systems. International Journal of Service and Knowledge Management, 4(2), 71–86. https://doi.org/10.52731/ijskm.v4.i2.574.

Jarque, C. M., & Bera, A. K. (1987). A Test For Normality Of Observations And Regression Residuals. International Statistical Review/ Revue Internationale de Statistique, 55(2), 163. https://doi.org/10.2307/1403192.

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(July), 105–116. https://doi.org/10.1016/j.irfa.2018.07.010.

Kołodziejczyk, H. (2023). Stablecoins As Diversifiers, Hedges And Safe Havens: A Quantile Coherency Approach. North American Journal of Economics and Finance, 66(January), 1–11. https://doi.org/10.1016/j.najef.2023.101912.

Kroner, K. F., & Sultan, J. (1993). Time-Varying Distributions And Dynamic Hedging With Foreign Currency Futures. The Journal of Financial and Quantitative Analysis, 28(4), 535. https://doi.org/10.2307/2331164.

Łęt, B., Sobański, K., Świder, W., & Włosik, K. (2023). What Drives The Popularity Of Stablecoins? Measuring The Frequency Dynamics Of Connectedness Between Volatile And Stable Cryptocurrencies. Technological Forecasting and Social Change, 189(November 2022). https://doi.org/10.1016/j.techfore.2023.122318.

Liu, H., Manzoor, A., Wang, C., Zhang, L., & Manzoor, Z. (2020). The COVID-19 Outbreak And Affected Countries Stock Markets Response. International Journal of Environmental Research and Public Health, 17(8), 1–19. https://doi.org/10.3390/ijerph17082800.

Lyons, R. K., & Viswanath-Natraj, G. (2023). What Keeps Stablecoins Stable? Journal of International Money and Finance, 131, 102777. https://doi.org/10.1016/j.jimonfin.2022.102777.

Okorie, D. I., & Lin, B. (2021). Stock Markets And The COVID-19 Fractal Contagion Effects. Finance Research Letters, 38(April 2020), 101640. https://doi.org/10.1016/j.frl.2020.101640.

Patton, A. J. (2006). Modelling Asymmetric Exchange Rate Dependence. International Economic Review, 47(2), 527–556. https://doi.org/10.1111/j.1468- 2354.2006.00387.x.

Sidorenko, E.L., (2020). Stablecoin As A New Financial Instrument. In: Ashmarina, S., Vochozka, M., Mantulenko, V. (Eds.), Digital Age: Chances, Challenges And Future. ISCDTE 2019. Lecture Notes in Networks and Systems, (84). Springer, Cham, 630–638. https://doi.org/10.1007/978-3-030-27015-5_75.

Sklar, M. (1959). Fonctions De Repartition An Dimensions Et Leurs Marges. 8. Publ. Inst. Statist (229–231). Univ. Paris.

Stensås, A., Nygaard, M. F., Kyaw, K., & Treepongkaruna, S. (2019). Can Bitcoin Be A Diversifier, Hedge Or Safe Haven Tool? Cogent Economics and Finance, 7(1). https://doi.org/10.1080/23322039.2019.1593072.

Wang, G. J., Ma, X. yu, & Wu, H. yu. (2020). Are Stablecoins Truly Diversifiers, Hedges, Or Safe Havens Against Traditional Cryptocurrencies As Their Name Suggests? Research in International Business and Finance, 54. https://doi.org/10.1016/j.ribaf.2020.101225.

Zaremba, A., Kizys, R., Aharon, D. Y., & Demir, E. (2020). Infected Markets: Novel Coronavirus, Government Interventions, And Stock Return Volatility Around The Globe. Finance Research Letters, 35. https://doi.org/10.1016/j.frl.2020.101597.

Zhang, W., He, X., & Hamori, S. (2022). Volatility Spillover And Investment Strategies Among Sustainability-Related Financial Indexes: Evidence From The DCC-GARCH-Based Dynamic Connectedness And DCC-GARCH T-Copula Approach. International Review of Financial Analysis, 83(May), 102223. https://doi.org/10.1016/j.irfa.2022.102223.