The Connection between DeFi, Oil, Gold, and the VIX Fear Index with Stock Markets in the Fragile Five Countries: A Wavelet Coherence Analysis

Year 2025, , 332 - 358, 28.03.2025

Nur Esra Bekereci , Aydın Gürbüz , Meltem Kılıç

https://doi.org/10.30784/epfad.1598165

Abstract

This study aims to examine the dynamic relationship between DeFi (decentralized finance) markets, commodity markets, fear index (VIX), and stock prices of fragile five countries (Brazil, India, Indonesia, Turkey, and South Africa) in time and frequency dimensions. Within the scope of the study, Link, Maker, and Basic Attention Token assets with the longest sample history representing DeFi markets between 2019-2024, oil and gold prices representing commodity markets, and the VIX fear index were used. The results obtained show that there is a positive correlation between DeFi, gold and oil markets, and stock returns of fragile five countries in different time periods. On the other hand, a negative relationship was found between the VIX index and stock indices of fragile five countries in the short, medium and long term. However, no clear finding was obtained regarding the leading relationship between the variables. These findings contribute to a better understanding of the effects of DeFi markets, commodity prices and VIX fear index on stock markets of fragile five countries. In particular, it was concluded that risk management strategies should be strengthened due to the hogh sensitivity of the fragile five countries to global market shocks.

Keywords

Fragile Five Stock Markets, Defi, Commodity Markets, Fear Index, Wavelet Transformation

DeFi, Petrol, Altın ve VIX Korku Endeksinin Kırılgan Beşli Ülkelerindeki Hisse Senedi Piyasalarıyla Bağlantısı: Bir Dalgacık Tutarlılığı Analizi

Abstract

Bu çalışma, DeFi (merkeziyetsiz finans) piyasaları, emtia piyasaları ve korku endeksi (VIX) ile kırılgan beşli ülkelerin (Brezilya, Hindistan, Endonezya, Türkiye ve Güney Afrika) borsa fiyatları arasındaki dinamik ilişkileri zaman ve frekans boyutunda incelemeyi amaçlamaktadır. Çalışma kapsamında 2019-2024 dönemi arasındaki DeFi piyasalarını temsilen en uzun örneklem geçmişine sahip olan Link, Maker ve Basic Attention Token varlıkları, emtia piyasalarını temsil eden petrol ve altın fiyatları ile VIX korku endeksi kullanılmıştır. Elde edilen sonuçlar, DeFi, altın ve petrol piyasaları ile kırılgan beşli ülkelerin hisse senedi getirileri arasında farklı zaman dilimlerinde pozitif bir korelasyon olduğunu göstermektedir. Öte yandan, VIX endeksi ile kırılgan beşli ülkelerin borsa endeksleri arasında kısa, orta ve uzun vadede negatif yönlü bir ilişki tespit edilmiştir. Ancak, değişkenler arasındaki öncülük ilişkisine dair belirgin bir bulgu elde edilememiştir. Bu bulgular, DeFi piyasaları, emtia fiyatları ve VIX korku endeksinin kırılgan beşli ülkelerinin borsa piyasaları üzerindeki etkilerini daha iyi anlamaya katkı sağlamaktadır. Özellikle, kırılgan beşli ülkelerin küresel piyasa şoklarına karşı duyarlılığının yüksek olması nedeniyle, risk yönetimi stratejilerinin güçlendirilmesi gerektiği sonucuna varılmıştır.

Keywords

Kırılgan Beşli Hisse Senedi Piyasaları, DeFi, Emtia Piyasaları, Korku Endeksi, Dalgacık Dönüşümü

References

• Aguiar-Conraria, L., Azevedo, N. and Soares, M.J. (2008). Using wavelets to decompose the time–frequency effects of monetary policy. Physica A: Statistical Mechanics and its Applications, 387(12), 2863-2878. https://doi.org/10.1016/j.physa.2008.01.063
• Al-Ameer, M., Hammad, W., Ismail, A. and Hamdan, A. (2018). The relationship of gold price with the stock market: The case of Frankfurt stock exchange. International Journal of Energy Economics and Policy, 8(5), 357-371. https://www.econjournals.com/
• Ali, M. and Khan, K. (2020). Volatility in discretionary public spending and economic growth. The Pakistan Development Review, 59(1), 45-68. https://www.jstor.org/stable/27184716
• Annamalaisamy, B. and Jayaraman, S.V. (2024). Do cryptocurrencies integrate with the indices of equity, sustainability, clean energy, and crude oil? A wavelet coherency approach. International Journal of Finance & Economics, 29(3), 3372–3392. https://doi.org/10.1002/ijfe.2843
• Asafo-Adjei, E., Agyapong, D., Agyei, S.K., Frimpong, S., Djimatey, R. and Adam, A.M. (2020). Economic policy uncertainty and stock returns of Africa: A wavelet coherence analysis. Discrete Dynamics in Nature and Society, 1, 8846507. https://doi.org/10.1155/2020/8846507
• Aydoğan, B., Vardar, G. and Taçoğlu, C. (2022). Volatility spillovers among G7, E7 stock markets and cryptocurrencies. Journal of Economic and Administrative Sciences, 40(2), 364-387. https://doi.org/10.1108/JEAS-09-2021-0190
• Badshah, I., Demirer, R. and Suleman, M.T. (2019). The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging. Energy Economics, 84, 104553. https://doi.org/10.1016/j.eneco.2019.104553
• Baur, D.G. and Lucey, B.M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. The Financial Review, 45(2), 217-229. https://doi.org/10.1111/j.1540-6288.2010.00244.x
• Bejaoui, A., Frikha, W., Jeribi, A. and Bariviera, A.F. (2023). Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Sonem new evidence from wavelet analysis. Physica A: Statistical Mechanics and its Applications, 619, 128720. https://doi.org/10.1016/j.physa.2023.128720
• Bouri, E., Gupta, R., Tiwari, A.K. and Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95. http://dx.doi.org/10.1016/j.frl.2017.02.009 1544-6123
• Bunget, O.C. and Lazea, G.I. (2023). Comparative analysis cryptocurrencies versus stocks. CECCAR Business Review, 4(11), 49-65. Retrieved from https://econpapers.repec.org/
• Caferra, R. and 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
• Cai, X.J., Tian, S., Yuan, N. and Hamori, S. (2017). Interdependence between oil and East Asian stock markets: Evidence from wavelet coherence analysis. Journal of International Financial Markets, Institutions & Money, 48, 206-223. https://doi.org/10.1016/j.intfin.2017.02.001
• Cheikh, N.B., Naceur, M.S.B., Kanaan, M.O. and Rault, C. (2018). Oil prices and GCC stock markets: New evidence from smooth transition models (CESifo Working Paper No. 7072). Retrieved from https://www.econstor.eu/bitstream/10419/180334/1/cesifo1_wp7072.pdf
• Chen, J., Cheng, Y. and Li, Y. (2022). The Russian-Ukraine conflict, crude oil price fluctuation and dynamic changes in stock market: Evidence from the U.S and China. BCP Business & Management, 30, 276-285. Retrieved from https://pdfs.semanticscholar.org/
• Chittineni, J. (2022). The nonlinear asymmetric relationship among implied volatility indices of Indian stock market, gold, and oil: Evidence from NARDL model. Indian Journal of Finance and Banking, 9(1), 1-9. https://doi.org/10.46281/ijfb.v9i1.1540
• Chohan, U.W. (2021). Decentralized finance (DeFi): An emergent alternative financial architecture (CBRI Working Papers No. 2021). Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3791921
• Choi, S.Y. (2020). Industry volatility and economic uncertainty due to the COVID-19 pandemic: Evidence from wavelet coherence analysis. Finance Research Letters, 37, 101783. https://doi.org/10.1016/j.frl.2020.101783
• Choi, K. and Hammoudeh, S. (2010). Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment. Energy Policy, 38, 4388-4399. https://doi.org/10.1016/j.enpol.2010.03.067
• Choi, S.Y. and Hong, C. (2020). Relationship between uncertainty in the oil and stock markets before and after the shale gas revolution: Evidence from the OVX, VIX, and VKOSPI volatility indices. PloS One, 15(5), e0232508. https://doi.org/10.1371/journal.pone.0232508
• Choudhry, T., Hassan, S.S. and Shabi, S. (2015). Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests. International Review of Financial Analysis, 41, 247-256. https://doi.org/10.1016/j.irfa.2015.03.011
• Coinmarketcap. (2024). Cryptocurrencies [Dataset]. Retrieved from www.coinmarketcap.com
• Corbet, S., Goodell, J.W. and Günay, S. (2022). What drives DeFi prices? Investigating the effects of investor attention, Finance Research Letters, 48, 102883. https://doi.org/10.1016/j.frl.2022.102883
• Coronado, S., Jimnez-Rodrguez, R. and Rojas, O. (2018). An empirical analysis of the relationships between crude oil, gold and stock markets. The Energy Journal, 39(1_suppl), 193-208. https://doi.org/10.5547/01956574.39.SI1.scor
• Cui, X., Goh, M., Li, B. and Zou, H. (2021). Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives. Energy, 216, 119302. https://doi.org/10.1016/j.energy.2020.119302
• Çevik, E.İ., Gunay, S., Zafar, M.W., Destek, M.A., Bugan, M.F. and Tuna, F. (2022). The impact of digital finance on the natural resource market: Evidence from DeFi, oil, and gold. Resources Policy, 79, 103081. https://doi.org/10.1016/j.resourpol.2022.103081
• Das, D. and Kannadhasan, M. (2018). Do global factors impact bitcoin prices? Evidence from wavelet approach. Journal of Economic Research, 23(3), 227-264. Retrieved from https://kiss.kstudy.com/
• Drake, P.P. (2022). The gold-stock market relationship during COVID-19. Finance Research Letters, 44, 102111. https://doi.org/10.1016/j.frl.2021.102111
• Eldomiaty, T. and Khaled, N. (2024). Cryptocurrency volatility and Egyptian stock market indexes: A note. Modern Finance, 2(1), 121-130. https://doi.org/10.61351/mf.v2i1.138
• Fareed, Z., Iqbal, N., Shahzad, F., Shah, S.G.M., Zulfiqar, B., Shahzad, K., Hasmi, S.H. and Shahzad, U. (2020). Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence. Air Quality, Atmosphere & Health, 13, 673-682. https://doi.org/10.1007/s11869-020-00847-1
• Frikha, W., Bejaoui, A., Bariviera, A.F. and Jeribi, A. (2024). What matters for comovements among gold, bitcoin, CO2, commodities, vix and international stock markets during the health, political and bank crises? Risks, 12(3), 47. https://doi.org/10.3390/risks12030047
• Ghallabi, F., Ghorbel, A., Kumar, S. and Sharif, A. (2024). Measuring risk transmission between international oil and islamic stock markets: A comparative analysis with the gold markets. International Review of Economics and Finance, 95, 103465. https://doi.org/10.1016/j.iref.2024.103465
• Ghazani, M.M. and Jafari, M.A. (2021). Cryptocurrencies, gold, and WTI crude oil market efficiency: A dynamic analysis based on the adaptive market hypothesis, Financial Innovation, 7(29), 1-26. https://doi.org/10.1186/s40854-021-00246-0
• Gnangnon, S.K. (2021). Productive capacities, economic growth and economic growth volatility in developing countries: Does structural economic vulnerability matter? Journal of International Commerce, Economics and Policy, Advance online publication. https://doi.org/10.20944/preprints202104.0491.v1
• Goupillaud, P., Grossmann, A. and Morlet, J. (1984). Cycle-octave and relatedtransforms in seismic signal analysis. Geoexploration, 23(1), 85-102. https://doi.org/10.1016/0016-7142(84)90025-5
• Grinsted, A., Moore, J.C. and Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophys, 11, 561-566. https://doi.org/10.5194/npg-11-561-2004
• Hamal, J.B. and Gautam, R.R. (2021). Capital market response to covid-19 pandemic–a systematic review on stock volatility and performance. Marsyangdi Journal, 2, 27-49. https://doi.org/10.3126/mj.v2i1.39963
• Hung, N.T. (2024). Price spillovers from decentralized finance to CEE stock markets. Politická Ekonomie, 72(3), 565-596. https://doi.org/10.18267/j.polek.1416
• Investing. (2024). Investing [Dataset]. Retrieved from https://investing.com/
• Jiang, C., Chang, T. and Li, X.L. (2015). Money growth and inflation in China: New evidence from a wavelet analysis. International Review of Economics & Finance, 35, 249-261. https://doi.org/10.1016/j.iref.2014.10.005
• Junior, P.O., Adam, A.M., Asafo-Adjei, E., Boateng, E., Hamidu, Z. and Awotwe, E. (2021). Time-frequency domain analysis of investor fear and expectations in stock markets of BRIC economies. Heliyon, 7(10), e08211. https://doi.org/10.1016/j.heliyon.2021.e08211
• Kang, S.H., McIver, R.P. and Hernandez, J.A. (2019). Co-movements between Bitcoin and Gold: A wavelet coherence analysis. Physica A: Statistical Mechanics and its Applications, 536, 120888. https://doi.org/10.1016/j.physa.2019.04.124
• Karabulut, T. ve Sarı, S.S. (2022). Nüfusa oranla kripto para yatırımcısı en çok ve en az olan ülkelerin borsa endeksi ile Bitcoin arasındaki ilişkinin incelenmesi. Alanya Akademik Bakış, 6(2), 2319-2332. https://doi.org/10.29023/alanyaakademik.1054246
• Kartal M.T., Kirikkaleli D. and Ayhan F. (2023). Nexus between non-performing loans and economic growth in emerging countries: Evidence from Turkey with wavelet coherence approach. International Journal of Finance & Economics, 28(2), 1250–1260. https://doi.org/10.1002/ijfe.2474
• Khan, M.N. (2024). Impact of COVID-19 crisis on volatility spillovers across global financial markets. Journal of Economic Integration, 39(2), 373-393. https://doi.org/10.11130/jei.2024005
• Kim, H. (2023). The impact of the COVID-19 pandemic on travel cryptocurrency and stock market performances: An event-study approach. Journal of Hospitality and Tourism Technology, 14(2), 172-187. https://doi.org/10.1108/JHTT-02-2022-0053
• Korsah, D., Amewu, G. and Osei Achampong, K. (2024). The impact of geopolitical risks, financial stress, economic policy uncertainty on African stock markets returns and volatilities: wavelet coherence analysis. Journal of Humanities and Applied Social Sciences, 6(5), 450-470. https://doi.org/10.1108/JHASS-12-2023-0172
• Kuhe, D.A. (2019). The dynamic relationship between crude oil prices and stock market price volatility in Nigeria: a cointegrated VAR-GARCH model. Current Journal of Applied Science and Technology, 38(3), 1-12. https://doi.org/10.9734/cjast/2019/v38i330363.
• Kumah, S.P. and Odei-Mensah, J. (2021). Are Cryptocurrencies and African stock markets integrated? The Quarterly Review of Economics and Finance, 81, 330-341. https://doi.org/10.1016/j.qref.2021.06.022
• Liao, X., Li, Q., Chan, S., Chu, J. and Zhang, Y. (2024). Interconnections and contagion among cryptocurrencies, DeFi, NFT, and traditional financial assets: Some new evidence from tail risk driven network. Physica A, 647, 129892. https://doi.org/10.1016/j.physa.2024.129892
• Madaleno, M. and Pinho, C. (2014). Wavelet dynamics for oil-stock world interactions. Energy Economics, 45, 120-133. https://doi.org/10.1016/j.eneco.2014.06.024
• Martens, M. and Poon, S.H. (2001). Returns synchronization and daily correlation dynamics between international stock markets. Journal of Banking & Finance, 25(10), 1805-1827. https://doi.org/10.1016/S0378-4266(00)00159-X
• Masih, M. and Majid, H.A. (2013). Comovement of selected international stock market indices: A continuous wavelet transformation and cross wavelet transformation analysis (MPRA Paper No. 58313). Retrieved from https://mpra.ub.uni-muenchen.de/58313/
• Mensi, W., Gubareva, M., Ko, H.U., Vo, X.V. and Kang, S.H. (2023). Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets. Financial Innovation, 9(92). https://doi.org/10.1186/s40854-023-00498-y
• Mudiangombe, B.M. and Mwamba, J.W.M. (2023). Dependence structure and time-frequency impact of exchange rates on crude oil and stock markets of BRICS countries: Markov-switching-based wavelet analysis. Journal of Risk and Financial Management, 16(319). https://doi.org/10.3390/jrfm16070319
• Muhammad, A., Ishaq, A.A., Mike, M.E.E., Ibitomi, T., Ishaq, N.A. and Isyaku, M. (2024). Decentralized Finance (DeFi) and traditional banking: A convergence or collision. Economics, Politics and Regional Development, 5(1), 1-14. https://doi.org/10.22158/eprd.v5n1p1
• Orhan, A., Kirikkaleli, D. and Ayhan, F. (2019). Analysis of wavelet coherence: Service sector index and economic growth in an emerging market. Sustainability, 11(23), 6684. https://doi.org/10.3390/su11236684
• Piotrkowski, R., Gallego, A., Castro, E., García-Hernandez, M.T. and Ruzzante, J.E. (2005). Ti and Cr nitride coating/steel adherence assessed by acoustic emission wavelet analysis. Ndt & E International, 38(4), 260-267. https://doi.org/10.1016/j.ndteint.2004.09.002
• Ramos, D. and Zanko, G. (2020). A review of the current state of decentralized finance as a subsector of the cryptocurrency market. Retrieved from https://static1.squarespace.com/static/553d790de4b08ceb08ab88fd/t/5f5c2a4d381d4c58ce97cde2/1599875662625/DeFi_P2_SciPaper_3.pdf
• Ramzan, M., Adebayo, T.S., Iqbal, H.A., Razi, U. and Wong, W.K. (2023). Analyzing the nexus between financial risk and economic risk in India: Evidence through the lens of wavelet coherence and non-parametric approaches. Heliyon, 9(3), e14180. https://doi.org/10.1016/j.heliyon.2023.e14180
• Raza, N., Ibrahimy, A.I., Ali, A. and Ali, S. (2016). Gold and islamic stocks: A hedge and safe haven comparison in time frequency domain for brics markets. The Journal of Developing Areas, 50(Special Issue). Retrieved from https://www.jstor.org/stable/26415668
• Reboredo, J.C., Rivera-Castro, M.A. and Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices. Energy Economics, 61, 241-252. https://doi.org/10.1016/j.eneco.2016.10.015
• Rösch, A. and Schmidbauer, H. (2018). WaveletComp 1.1: A guided tour through the R package. Retrieved from http://www.hs-stat.com/projects/WaveletComp/WaveletComp_guided_tour.pdf
• Rua, A. and Nunes, L.C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16, 632-639. https://doi.org/10.1016/j.jempfin.2009.02.002
• Sarwar, G. (2017). Examining the Flight-to-safety with the implied volatilities. Finance Research Letters, 20, 118-124. http://dx.doi.org/10.1016/j.frl.2016.09.015
• Sarwar, G. and Khan, W. (2017) The effect of US stock market uncertainty on emerging market returns. Emerging Markets Finance and Trade, 53(8), 1796-1811. https://doi.org/10.1080/1540496X.2016.1180592
• Schär, F. (2021). Decentralized finance: on blockchain and smart contract-based financial markets. Review of the Federal Reserve Bank of St Louis, 103(2), 153-174. https://doi.org/10.20955/r.103.153-74
• Shabbir, A., Kousar, S. and Batool, S.A. (2020). Impact of gold and oil prices on the stock market in Pakistan. Journal of Economics, Finance and Administrative Science, 25(50), 279-294. https://doi.org/10.1108/JEFAS-04-2019-0053
• Shaikh, I. (2018). Investors’ fear and stock returns: Evidence from national stock exchange of India. Engineering Economics, 29(1), 4-12. https://doi.org/10.5755/j01.ee.29.1.14966
• Shi, Y., Yang, L., Huang, M. and Huang, J.S. (2021). Multi-factorized semi-covariance of stock markets and gold price. Journal of Risk and Financial Management, 14(4), 172. https://doi.org/10.3390/jrfm14040172
• Siddiqui, S. and Roy, P. (2019). Predicting volatility and dynamic relation between stock market, exchange rate and select commodities. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 67(6), 1597-1611. https://doi.org/10.11118/actaun201967061597
• Şoiman, F., Dumas, J-C. and Jimenez-Garces, S. (2023). What drices DeFi market returns? Journal of International Financial Markets, Institutions & Money, 85, 101786. https://doi.org/10.1016/j.intfin.2023.101786
• Torrence, C. and Compo, G.P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79, 61-78. https://doi.org/10.1175/1520-0477(1998)079%3C0061:APGTWA%3E2.0.CO;2
• Torrence, C. and Webster, P.J. (1999). Interdecadal changes in the enso-monsoon system. Journal of Climate, 12(8), 2679-2690. https://doi.org/10.1175/1520-0442(1999)012%3C2679:ICITEM%3E2.0.CO;2
• Ugolini, A., Reboredo, J.C. and Mensi, W. (2023). Connectedness between DeFi, Cryptocurrency, stock and safe-haven assets. Finance Research Letters, 53, 103692. https://doi.org/10.1016/j.frl.2023.103692
• Uludağ, B.K. and Khurshid, M. (2019). Volatility spillover from the Chinese stock market to E7 and G7 stock markets. Journal of Economic Studies, 46(1), 90-105. https://doi.org/10.1108/JES-01-2017-0014
• Vacha, L. and Barunik, J. (2012). Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis. Energy Economics, 34, 241-247. https://doi.org/10.1016/j.eneco.2011.10.007
• Wang, J., Zhu, J. and Dou, F. (2012). Who plays the key role among Shanghai, Shenzhen and Hong Kong stock markets? China & World Economy, 20(6), 102-120. https://doi.org/10.1111/j.1749-124X.2012.12004.x
• Wu, K., Zhu, J., Xu, M. and Yang, L. (2020). Can crude oil drive the co-movement in the international stock market? Evidence from partial wavelet coherence analysis. The North American Journal of Economics and Finance, 53, 101194. https://doi.org/10.1016/j.najef.2020.101194
• Yang, L., Cai, X. J., Zhang, H. and Hamori, S. (2016). Interdependence of foreign exchange markets: A wavelet coherence analysis. Economic Modelling, 55, 6-14. https://doi.org/10.1016/j.econmod.2016.01.022
• Ye, Z., Hu, C., He., Ouyang, G. and Wen, F. (2020). The dynamic time-frequency relationship between international oil prices and investor sentiment in China: A wavelet coherence analysis. The Energy Journal, 41(5), 251-270. https://doi.org/10.5547/01956574.41.5.fwen
• Yen, N.H. and Ha, L.T. (2023). Interlinkages of cryptocurrency and stock markets during the COVID-19 pandemic by applying a QVAR model. European Journal of Management and Business Economics, 33(1), 74-95. https://doi.org/10.1108/EJMBE-02-2022-0035
• Yılancı, V. and Pata, U.K. (2023). COVID-19, stock prices, exchange rates and sovereign bonds: A wavelet-based analysis for Brazil and India. International Journal of Emerging Markets, 18(11), 4968-4986. https://doi.org/10.1108/IJOEM-09-2021-1465
• Yousaf, I. and Yarovaya, L. (2022) Herding behavior in conventional cryptocurrency market, non-fungible tokens and DeFi assets. Finance Research Letters, 50, 103299. https://doi.org/10.1016/j.frl.2022.103299
• Yousaf, I., Jareno, F. and Tolentino, M. (2023). Connectedness between DeFi assets and equity markets during COVID-19: A sector analysis. Technological Forecasting & Social Change, 187, 122174. https://doi.org/10.1016/j.techfore.2022.122174
• Youssef, M. and Mokni, K. (2019). Do crude oil prices drive the relationship between stock markets of oil-importing and oil-exporting countries? Economies, 7(3), 70. https://doi.org/10.3390/economies7030070
• Zetzsche, D.A., Arner, D.W. and Buckley, R.P. (2020). Decentralized finance. Journal of Financial Regulation, 6(2), 172-203. https://doi.org/10.1093/jfr/fjaa010
• Zhou, J. (2010). Comovement of international real estate securities returns: A wavelet analysis. Journal of Property Research, 27(4), 357-373. https://doi.org/10.1080/09599916.2010.517853