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General & Applied Economics

Unveiling the interlinkage between Ethereum and Nifty indices: impact of cryptocurrency on Indian equity markets post Covid-19

, ORCID Icon, ORCID Icon & ORCID Icon
Article: 2359599 | Received 13 Oct 2023, Accepted 17 May 2024, Published online: 23 Jun 2024

References

  • Adebola, S. S., Gil-Alana, L. A., & Madigu, G. (2019). Gold prices and the cryptocurrencies: Evidence of convergence and cointegration. Physica A: Statistical Mechanics and Its Applications, 523, 1227–1236. https://doi.org/10.1016/j.physa.2019.04.123
  • Adjasi, C. K. d., Biekpe, N. B., & Osei, K. A. (2011). Stock prices and exchange rate dynamics in selected African countries: a bivariate analysis. African Journal of Economic and Management Studies, 2(2), 143–164. https://doi.org/10.1108/20400701111165623
  • Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838–851. https://doi.org/10.1016/j.eneco.2009.05.016
  • Alexander, C., & Dakos, M. (2020). A critical investigation of cryptocurrency data and analysis. Quantitative Finance, 20(2), 173–188. https://doi.org/10.1080/14697688.2019.1641347
  • Angela, O., & Sun, Y. (2020). Factors affecting cryptocurrency prices: Evidence from Ethereum. Proceedings of 2020 International Conference on Information Management and Technology, ICIMTech 2020 (pp. 318–323). IEEE. https://ieeexplore.ieee.org/document/9211195
  • Aras, S. (2021). Stacking hybrid GARCH models for forecasting Bitcoin volatility. Expert Systems with Applications, 174, 114747. https://doi.org/10.1016/j.eswa.2021.114747
  • Aravind, M. (2017). FX volatility impact on Indian stock market: An empirical investigation. Vision, 21(3), 284–294. https://doi.org/10.1177/0972262917716760
  • Aydoğan, B., Tunç, G., & Yelkenci, T. (2017). The impact of oil price volatility on net-oil exporter and importer countries’ stock markets. Eurasian Economic Review, 7(2), 231–253. https://doi.org/10.1007/S40822-017-0065-1/TABLES/5
  • Bagci, H., & Koylu, M. K. (2019). Cryptocurrency: Determining the correlation between Bitcoin cryptocurrency and gold prices. In Fatih Ayhan, Burak Darici (Eds.), Cryptocurrency in all aspects (pp. 193–206).https://www.peterlang.com/document/1110947#:∼:text=Summary,expert%20researchers%20in%20their%20fields
  • Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D. (2017). Can volume predict Bitcoin returns and volatility? A quantiles-based approach. Economic Modelling, 64, 74–81. https://doi.org/10.1016/j.econmod.2017.03.019
  • Beckmann, J., & Czudaj, R. (2013). Is there a homogeneous causality pattern between oil prices and currencies of oil importers and exporters? Energy Economics, 40, 665–678. https://doi.org/10.1016/j.eneco.2013.08.007
  • Beckmann, J., Czudaj, R., & Pilbeam, K. (2015). Causality and volatility patterns between gold prices and exchange rates. The North American Journal of Economics and Finance, 34, 292–300. https://doi.org/10.1016/j.najef.2015.09.015
  • Blau, B. M. (2017). Price dynamics and speculative trading in bitcoin. Research in International Business and Finance, 41, 493–499. https://doi.org/10.1016/j.ribaf.2017.05.010
  • Bouri, E., Jain, A., Biswal, P. C., & Roubaud, D. (2017). Cointegration and non-linear causality amongst gold, oil, and the Indian stock market: Evidence from implied volatility indices. Resources Policy, 52, 201–206. https://doi.org/10.1016/j.resourpol.2017.03.003
  • Bouri, E., Roubaud, D., Jammazi, R., & Assaf, A. (2017). Uncovering frequency domain causality between gold and the stock markets of China and India: Evidence from implied volatility indices. Finance Research Letters, 23, 23–30. https://doi.org/10.1016/j.frl.2017.06.010
  • Bouri, E., Gupta, R., Lahiani, A., & Shahbaz, M. (2018). Testing for asymmetric non-linear short- and long-run relationships between bitcoin, aggregate commodity and gold prices. Resources Policy, 57, 224–235. https://doi.org/10.1016/j.resourpol.2018.03.008
  • Caferra, R., & Vidal-Tomás, D. (2021). Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic. Finance Research Letters, 43, 101954. https://doi.org/10.1016/j.frl.2021.101954
  • Chien, F. S., Sadiq, M., Kamran, H. W., Nawaz, M. A., Hussain, M. S., & Raza, M. (2021). Co-movement of energy prices and stock market return: Environmental wavelet nexus of COVID-19 pandemic from the USA, Europe, and China. Environmental Science and Pollution Research, 28(25), 32359–32373. https://doi.org/10.1007/S11356-021-12938-2/TABLES/4
  • Diks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30(9–10), 1647–1669. https://doi.org/10.1016/j.jedc.2005.08.008
  • Elsayed, A. H., Gozgor, G., & Yarovaya, L. (2022). Volatility and return connectedness of cryptocurrency, gold, and uncertainty: Evidence from the cryptocurrency uncertainty indices. Finance Research Letters, 47, 102732. https://doi.org/10.1016/j.frl.2022.102732
  • Farooq, M. T., Keung, W. W., & Kazmi, A. A. (2004). Linkage between stock market prices and exchange rate: A causality analysis for Pakistan. The Pakistan Development Review, 43(4II), 639–649. https://doi.org/10.2307/41261018
  • Frenkel, J. A., & Rodriguez, C. A. (1975). Portfolio equilibrium and the balance of payments: A monetary approach. The American Economic Review, 65(4), 674–688. https://doi.org/10.2307/1806543
  • Gambarelli, L., Marchi, G., & Muzzioli, S. (2023). Hedging effectiveness of cryptocurrencies in the European stock market. Journal of International Financial Markets, Institutions and Money, 84, 101757. https://doi.org/10.1016/j.intfin.2023.101757
  • 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
  • Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. https://doi.org/10.2307/1912791
  • Ha, L. T. (2023). Interlinkages of cryptocurrency and stock markets during COVID-19 pandemic by applying a TVP-VAR extended joint connected approach. Journal of Economic Studies, 50(3), 407–428. https://doi.org/10.1108/JES-01-2022-0055
  • Hamouda, F. (2021). Identifying economic shocks with stock repurchase programs. Cogent Economics & Finance, 9(1), 1968112. https://doi.org/10.1080/23322039.2021.1968112
  • Han, H., Linton, O., Oka, T., & Whang, Y. J. (2016). The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series. Journal of Econometrics, 193(1), 251–270. https://doi.org/10.1016/j.jeconom.2016.03.001
  • Hiemstra, C., & Jones, J. D. (1994). Testing for linear and non-linear Granger causality in the stock price-volume relation. The Journal of Finance, 49(5), 1639–1664. https://doi.org/10.2307/2329266
  • Huynh, T. L. D., Nasir, M. A., Vo, X. V., & Nguyen, T. T. (2020). “Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet. The North American Journal of Economics and Finance, 54, 101277. https://doi.org/10.1016/j.najef.2020.101277
  • Ingalhalli, V., Poornima, B. G., & Reddy, Y. V. (2016). A study on dynamic relationship between oil, gold, FOREX and stock markets in Indian context. Paradigm, 20(1), 83–91. https://doi.org/10.1177/0971890716637706
  • Koshelev, K. A. (2022). Trends in the evolution of the digital financial assets market in the context of the digital transformation of the global economy. Finance: Theory and Practice, 26(4), 80–94. https://doi.org/10.26794/2587-5671-2022-26-4-80-9
  • Lahmiri, S., & Bekiros, S. (2020). The impact of COVID-19 pandemic upon stability and sequential irregularity of equity and cryptocurrency markets. Chaos, Solitons, and Fractals, 138, 109936. https://doi.org/10.1016/j.chaos.2020.109936
  • Kamal, M. R., & Wahlstrøm, R. R. (2023). Cryptocurrencies and the threat versus the act event of geopolitical risk. Finance Research Letters, 57, 104224. https://doi.org/10.1016/j.frl.2023.104224
  • Kim, M. J., Canh, N. P., & Park, S. Y. (2021). Causal relationship among cryptocurrencies: A conditional quantile approach. Finance Research Letters, 42, 101879. https://doi.org/10.1016/j.frl.2020.101879
  • 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
  • Kliber, A., Marszałek, P., Musiałkowska, I., & Świerczyńska, K. (2019). Bitcoin: Safe haven, hedge or diversifier? Perception of bitcoin in the context of a country’s economic situation—a stochastic volatility approach. Physica A: Statistical Mechanics and Its Applications, 524, 246–257. https://doi.org/10.1016/j.physa.2019.04.145
  • Kristjanpoller, W., Bouri, E., & Takaishi, T. (2020). Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis. Physica A: Statistical Mechanics and Its Applications, 545, 123711. https://doi.org/10.1016/j.physa.2019.123711
  • Mahdi, E., Leiva, V., Mara’Beh, S., & Martin-Barreiro, C. (2021). A new approach to predicting cryptocurrency returns based on the gold prices with support vector machines during the COVID-19 pandemic using sensor-related data. Sensors, 21(18), 6319. https://doi.org/10.3390/S21186319
  • Matha, R., E. G., Kumar, S., & Raghavendra. (2022). Dynamic relationship between equity, bond, commodity, forex and foreign institutional investments: Evidence from India. Investment Management and Financial Innovations, 19(4), 65–82. https://doi.org/10.21511/IMFI.19(4).2022.06
  • Mensi, W., Gubareva, M., Ko, H. U., Vo, X. V., & Kang, S. H. (2023). Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets. Financial Innovation, 9(1), 92. https://doi.org/10.1186/s40854-023-00498-y
  • Noman, A. H. M., Karim, M. M., Hassan, M. K., Khan, M. A., & Pervin, S. (2023). COVID-19 pandemic and the dynamics of major investable assets: What gives shelter to investors? International Review of Economics & Finance, 86, 14–30. https://doi.org/10.1016/j.iref.2023.03.003
  • Nyakurukwa, K., & Seetharam, Y. (2023). Stock market integration in Africa: Further evidence from an information‐theoretic framework. International Finance, 26(1), 2–18. https://doi.org/10.1111/infi.12419
  • Omri, I. (2023). Directional predictability and volatility spillover effect from stock market indexes to Bitcoin: Evidence from developed and emerging markets. The Journal of Risk Finance, 24(2), 226–243. https://doi.org/10.1108/JRF-06-2022-0130
  • Omrı, I., & Ozcelebı, O. (2023). Examination of the impacts of cryptocurrency uncertainty on exchange-traded funds. Singapore Economic Review, https://doi.org/10.1142/S0217590823500509
  • Parsva, P., & Tang, C. F. (2017). A note on the interaction between stock prices and exchange rates in Middle-East economies. Ekonomska Istraživanja [Economic Research}, 30(1), 836–844. https://doi.org/10.1080/1331677X.2017.1311222
  • Patel, R. J. (2017). Co-movement and integration among stock markets : A study of 14 countries. Indian Journal of Finance, 11(9), 53–66. https://doi.org/10.17010/ijf/2017/v11i9/118089
  • Ross, S. A. (2013). The arbitrage theory of capital asset pricing, 11–30.https://www.worldscientific.com/doi/abs/10.1142/9789814417358_0001
  • Saxena, S. P., & Bhadauriya, S. (2012). Causal analysis of oil prices and macroeconomic performance: Evidence from India. Asia-Pacific Journal of Management Research and Innovation, 8(4), 451–459. https://doi.org/10.1177/2319510X13481904
  • Shilov, K. D., & Zubarev, A. V. (2021). Evolution of Bitcoin as a financial asset. Finance: Theory and Practice, 25(5), 150–171. https://doi.org/10.26794/2587-5671-2021-25-5-150-171
  • Singh, N. P., & Sharma, S. (2018). Cointegration and causality among dollar, oil, gold and sensex across global financial crisis. Vision, 22(4), 365–376. https://doi.org/10.1177/0972262918804336
  • Thampanya, N., Nasir, M. A., & Huynh, T. L. D. (2020). Asymmetric correlation and hedging effectiveness of gold & cryptocurrencies: From pre-industrial to the 4th industrial revolution. Technological Forecasting and Social Change, 159, 120195. https://doi.org/10.1016/J.TECHFORE.2020.120195
  • Tudor, C., & Popescu-Dutaa, C. (2012). On the causal relationship between stock returns and exchange rates changes for 13 developed and emerging markets. Procedia - Social and Behavioral Sciences, 57, 275–282. https://doi.org/10.1016/j.sbspro.2012.09.1186
  • Vidal-Tomás, D., Briola, A., & Aste, T. (2023). FTX’s downfall and Binance’s consolidation: The fragility of centralised digital finance. Physica A: Statistical Mechanics and Its Applications, 625, 129044. https://doi.org/10.1016/j.physa.2023.129044
  • Wei, L., Lee, M. C., Cheng, W. H., Tang, C. H., & You, J. W. (2023). Evaluating the efficiency of financial assets as hedges against Bitcoin risk during the COVID-19 pandemic. Mathematics, 11(13), 2917. https://doi.org/10.3390/math11132917
  • Xunfa, L. U., Liu, S. K., San Liang, X., Zhang, Z., & Hairong, C. U. I. (2020). The break point-dependent causality between the cryptocurrency and emerging stock markets. Economic Computation and Economic Cybernetics Studies and Research, 54(4/2020), 203–216. https://doi.org/10.24818/18423264/54.4.20.13
  • Yang, J., De Montigny, D., & Treleaven, P. (2022). ANN, LSTM, and SVR for Gold Price Forecasting. 2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CIFEr 2022 - Proceedings. https://doi.org/10.1109/CIFER52523.2022.9776141
  • Yarovaya, L., Matkovskyy, R., & Jalan, A. (2021). The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets. Journal of International Financial Markets, Institutions and Money, 75, 101321. https://doi.org/10.1016/j.intfin.2021.101321