Predictive directional measurement volatility spillovers between the US and selected Asian Pacific countries

References

• Abdulrazzaq, Y. M., Morales, L., & Coughlan, J. (2019). Oil sector spillover effects to the Kuwait stock market in the context of uncertainty. Economics, Management & Financial Markets, 14, 1. https://www.ceeol.com/search/article-detail?id=752535
   Google Scholar
• Aboura, S., & Chevallier, J. (2014). Volatility equicorrelation: A cross-market perspective. Economics Letters, 122(2), 289–38. https://doi.org/10.1016/j.econlet.2013.12.008
   Web of Science ®Google Scholar
• Ahmed, R. I., Zhao, G., & Habiba, U. (2022). Dynamics of return linkages and asymmetric volatility spillovers among Asian emerging stock markets. The Chinese Economy, 55(2), 156–167. https://doi.org/10.1080/10971475.2021.1930292
   Google Scholar
• Aielli, G. P. (2013). Dynamic conditional correlation: On properties and estimation. Journal of Business & Economic Statistics, 31(3), 282–299. https://doi.org/10.1080/07350015.2013.771027
   Web of Science ®Google Scholar
• Arif, M., Naeem, M. A., Farid, S., Nepal, R., & Jamasb, T. (2022). Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19. Energy Policy, 168, 113102. https://doi.org/10.1016/j.enpol.2022.113102
   Web of Science ®Google Scholar
• Arouri, M. E. H., Jouini, J., & Nguyen, D. K. (2011). Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management. Journal of International Money and Finance, 30(7), 1387–1405. https://doi.org/10.1016/j.jimonfin.2011.07.008
   Web of Science ®Google Scholar
• Athari, S. A., & Hung, N. T. (2022). Time–frequency return co-movement among asset classes around the COVID-19 outbreak: Portfolio implications. Journal of Economics and Finance, 46(4), 736–756. https://doi.org/10.1007/s12197-022-09594-8
   Google Scholar
• Athari, S. A., Kondoz, M., & Kirikkaleli, D. (2021). Dependency between sovereign credit ratings and economic risk: Insight from Balkan countries. Journal of Economics and Business, 116, 105984. https://doi.org/10.1016/j.jeconbus.2021.105984
   Web of Science ®Google Scholar
• Baele, L., Ferrando, A., Hördahl, P., Krylova, E., & Monnet, C. (2004). Measuring European financial integration. Oxford Review of Economic Policy, 20(4), 509–530. https://doi.org/10.1093/oxrep/grh030
   Web of Science ®Google Scholar
• Baig, T., & Goldfajn, I. (1999). Financial market contagion in the Asian crisis. IMF Staff Papers, 46(2), 167–195. https://doi.org/10.2307/3867666
   Google Scholar
• Bala, D. A., & Takimoto, T. (2017). Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach. Borsa Istanbul Review, 17(1), 25–48. https://doi.org/10.1016/j.bir.2017.02.002
   Web of Science ®Google Scholar
• Bekaert, G., & Harvey, C. R. (1995). Time‐varying world market integration. the Journal of Finance, 50(2), 403–444. https://doi.org/10.1111/j.1540-6261.1995.tb04790.x
   Web of Science ®Google Scholar
• Bekaert, G., & Hodrick, R. J. (1992). Characterizing predictable components in excess returns on equity and foreign exchange markets. The Journal of Finance, 47(2), 467–509. https://doi.org/10.1111/j.1540-6261.1992.tb04399.x
   Web of Science ®Google Scholar
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
   Web of Science ®Google Scholar
• Bonilla, C. A., & Sepúlveda, J. (2011). Stock returns in emerging markets and the use of GARCH models. Applied Economics Letters, 18(14), 1321–1325. https://doi.org/10.1080/13504851.2010.537615
   Web of Science ®Google Scholar
• Campbell, J. Y., & Hamao, Y. (1992). Predictable stock returns in the United States and Japan: A study of long‐term capital market integration. The Journal of Finance, 47(1), 43–69. https://doi.org/10.1111/j.1540-6261.1992.tb03978.x
   Web of Science ®Google Scholar
• Caporale, G. M., Pittis, N., & Spagnolo, N. (2006). Volatility transmission and financial crises. Journal of Economics and Finance, 30(3), 376–390. https://doi.org/10.1007/BF02752742
   Google Scholar
• Cashin, M. P., Kumar, M. M. S., & McDermott, M. C. J. (1995). International integration of equity markets and contagion effects. International Monetary Fund.
   Google Scholar
• Chan, K. C., Fung, H. G., & Leung, W. K. (2004). Daily volatility behavior in Chinese futures markets. Journal of International Financial Markets, Institutions and Money, 14(5), 491–505. https://doi.org/10.1016/j.intfin.2004.01.002
   Google Scholar
• Chen, J., & Wang, X. (2021). Asymmetric risk spillovers between China and ASEAN Stock Markets. IEEE Access, 9, 141479–141503. https://doi.org/10.1109/ACCESS.2021.3119932
   Web of Science ®Google Scholar
• Cheung, Y. L., Cheung, Y. W., & Ng, C. C. (2007). East Asian equity markets, financial crises, and the Japanese currency. Journal of the Japanese and International Economies, 21(1), 138–152. https://doi.org/10.1016/j.jjie.2005.11.003
   Web of Science ®Google Scholar
• Chou, M. R. Y. T., Ng, M. V., & Pi, L. K. (1994). Cointegration of international stock market indices. International Monetary Fund.
   Google Scholar
• Christensen, B. J., & Nielsen, M. Ø. (2007). The effect of long memory in volatility on stock market fluctuations. The Review of Economics and Statistics, 89(4), 684–700. https://doi.org/10.1162/rest.89.4.684
   Web of Science ®Google Scholar
• Clark, P. K. (1973). A subordinated stochastic process model with finite variance for speculative prices. Econometrica: Journal of the Econometric Society, 41(1), 135–155. https://doi.org/10.2307/1913889
   Web of Science ®Google Scholar
• Click, R. W., & Plummer, M. G. (2005). Stock market integration in ASEAN after the Asian financial crisis. Journal of Asian Economics, 16(1), 5–28. https://doi.org/10.1016/j.asieco.2004.11.018
   Google Scholar
• 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
   Web of Science ®Google Scholar
• Dungey, M., Milunovich, G., & Thorp, S. (2010). Unobservable shocks as carriers of contagion. Journal of Banking & Finance, 34(5), 1008–1021. https://doi.org/10.1016/j.jbankfin.2009.11.006
   Web of Science ®Google Scholar
• Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487
   Web of Science ®Google Scholar
• Engle, R., & Kelly, B. (2012). Dynamic equicorrelation. Journal of Business & Economic Statistics, 30(2), 212–228. https://doi.org/10.1080/07350015.2011.652048
   Web of Science ®Google Scholar
• Engle, R. F., Ng, V. K., & Rothschild, M. (1990). Asset pricing with a factor-ARCH covariance structure: Empirical estimates for treasury bills. Journal of Econometrics, 45(1–2), 213–237. https://doi.org/10.1016/0304-4076(90)90099-F
   Web of Science ®Google Scholar
• Eun, C. S., & Shim, S. (1989). International transmission of stock market movements. Journal of Financial and Quantitative Analysis, 24(2), 241–256. https://doi.org/10.2307/2330774
   Web of Science ®Google Scholar
• Favero, C. A., & Giavazzi, F. (2002). Is the international propagation of financial shocks non-linear?: Evidence from the ERM. Journal of International Economics, 57(1), 231–246. https://doi.org/10.1016/S0022-1996(01)00139-8
   Web of Science ®Google Scholar
• Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market co-movements. The Journal of Finance, 57(5), 2223–2261. https://doi.org/10.1111/0022-1082.00494
   Web of Science ®Google Scholar
• Fujiwara, I., & Takahashi, K. (2012). Asian financial linkage: Macro‐finance dissonance. Pacific Economic Review, 17(1), 136–159. https://doi.org/10.1111/j.1468-0106.2011.00575.x
   Web of Science ®Google Scholar
• Gębka, B. (2012). The dynamic relation between returns, trading volume, and volatility: Lessons from spillovers between Asia and the United States. Bulletin of Economic Research, 64(1), 65–90. https://doi.org/10.1111/j.1467-8586.2010.00371.x
   Web of Science ®Google Scholar
• Gong, X., Liu, Y., & Wang, X. (2021). Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method. International Review of Financial Analysis, 76, 101790. https://doi.org/10.1016/j.irfa.2021.101790
   Web of Science ®Google Scholar
• Granger, C. W. J. (1986). Developments in the study of cointegrated economic variables. Oxford Bulletin of economics and statistics, 48(3), 213–228.
   Google Scholar
• Gulzar, S., Mujtaba Kayani, G., Xiaofen, H., Ayub, U., & Rafique, A. (2019). Financial cointegration and spillover effect of global financial crisis: A study of emerging Asian financial markets. Economic research-Ekonomska istraživanja, 32(1), 187–218. https://doi.org/10.1080/1331677X.2018.1550001
   Web of Science ®Google Scholar
• Hagstrom, R. G. (2013). The Warren Buffett Way. John Wiley & Sons.
   Google Scholar
• Hamao, Y., Masulis, R. W., & Ng, V. (1990). Correlations in price changes and volatility across international stock markets. The Review of Financial Studies, 3(2), 281–307. https://doi.org/10.1093/rfs/3.2.281
   Web of Science ®Google Scholar
• Harrison, B., & Moore, W. (2009). Stock market co-movement in the European Union and transition countries. Financial Studies, 3, 2–28. https://d1wqtxts1xzle7.cloudfront.net/8336059/vol13i3p124-151-libre.pdf?1390855067=&response-content-disposition=inline%3B+filename%3DSTOCK_MARKET_COMOVEMENT_IN_THE_EUROPEAN.pdf&Expires=1675540577&Signature=Sh42mtB6x-EaAytViyXVxfp8mrKLS3aJwL~clAYMs1e-X76Vhpo-zIYeDSaLglgCTXuXQKqqyATCZ7sIESv4HAOvCKo6-2w-TWeGl59Vn3xAcculsFG-ZTpD5sZj-HT6S2ds2Hb2-Q5YQyS6raFqXl2wLn6LqkwaWmO1LephGwJyQb6K4O-u0Jq619ZuUZLn0HF-XdB2vcVJNesBj2n9wpnr3BtAlPGlhYkbm~V52KjfVaQpoTXYPQPAxKq1T9UYa6Vb2TSeL5vGc-PlpGRcHRAlE3luY1vOEmoInol1VzpRK613tK3SPX-vUSFUXV9W7x2-5PF~KpYqQPvpC-5pxg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA
   Google Scholar
• Hong, D., Lee, C., & Swaminathan, B. (2003). Earnings momentum in international markets
   Google Scholar
• Hong, Y., Liu, Y., & Wang, S. (2009). Granger causality in risk and detection of extreme risk spillover between financial markets. Journal of Econometrics, 150(2), 271–287. https://doi.org/10.1016/j.jeconom.2008.12.013
   Web of Science ®Google Scholar
• Hong, H., Torous, W., & Valkanov, R. (2002). Do Industries Lead the Stock Market? Gradual Diffusion of Information and Cross-Asset Return Predictability. Finance. Retrieved from https://escholarship.org/uc/item/6x49x543
   Google Scholar
• Hung, N. T., & Vo, X. V. (2021). Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak. International Review of Financial Analysis, 76, 101730. https://doi.org/10.1016/j.irfa.2021.101730
   PubMed Web of Science ®Google Scholar
• Hussain, S. I., Nur-Firyal, R., & Ruza, N. (2022). Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases. Journal of Commodity Markets, 28, 100236. https://doi.org/10.1016/j.jcomm.2021.100236
   Google Scholar
• Hwang, J. K. (2014). Spillover effects of the 2008 financial crisis in Latin America stock markets. International Advances in Economic Research, 20(3), 311–324. https://doi.org/10.1007/s11294-014-9472-1
   Google Scholar
• Hwang, S., & Satchell, S. E. (2010). How loss averse are investors in financial markets? J. Bank. Finance, 34(10), 2425–2438. https://doi.org/10.1016/j.jbankfin.2010.03.018
   Web of Science ®Google Scholar
• Jebran, K., Chen, S., Ullah, I., & Mirza, S. S. (2017). Does volatility spillover among stock markets varies from normal to turbulent periods? Evidence from emerging markets of Asia. The Journal of Finance and Data Science, 3(1–4), 20–30. https://doi.org/10.1016/j.jfds.2017.06.001
   Google Scholar
• Kang, S. H., Uddin, G. S., Troster, V., & Yoon, S. M. (2019). Directional spillover effects between ASEAN and world stock markets. Journal of Multinational Financial Management, 52, 100592. https://doi.org/10.1016/j.mulfin.2019.100592
   Web of Science ®Google Scholar
• Kannadas, S., & Viswanathan, T. (2022). Volatility spillover effects among gold, oil and stock markets: Empirical evidence from the g7 countries. Economic Studies, 31(4). https://www.ceeol.com/search/article-detail?id=1040745
   Google Scholar
• King, M. A., & Wadhwani, S. (1990). Transmission of volatility between stock markets. The Review of Financial Studies, 3(1), 5–33. https://doi.org/10.1093/rfs/3.1.5
   Web of Science ®Google Scholar
• Kirikkaleli, D., & Athari, S. A. (2020). Time-frequency co-movements between bank credit supply and economic growth in an emerging market: Does the bank ownership structure matter? The North American Journal of Economics and Finance, 54, 101239. https://doi.org/10.1016/j.najef.2020.101239
   Web of Science ®Google Scholar
• Kondoz, M., Bora, I., Kirikkaleli, D., & Athari, S. (2019). Testing the volatility spillover between crude oil price and the US stock market returns. Management Science Letters, 9(8), 1221–1230. https://doi.org/10.5267/j.msl.2019.4.019
   Google Scholar
• Kondoz, M., Kirikkaleli, D., & Athari, S. A. (2021). Time-frequency dependencies of financial and economic risks in South American countries. The Quarterly Review of Economics and Finance, 79, 170–181. https://doi.org/10.1016/j.qref.2020.05.014
   Web of Science ®Google Scholar
• Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
   Web of Science ®Google Scholar
• Kroner, K. F., & Ng, V. K. (1998). Modeling asymmetric co-movements of asset returns. The Review of Financial Studies, 11(4), 817–844. https://doi.org/10.1093/rfs/11.4.817
   Web of Science ®Google Scholar
• 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), 535–551.
   Web of Science ®Google Scholar
• Ku, Y. H. H., Chen, H. C., & Chen, K. H. (2007). On the application of the dynamic conditional correlation model in estimating optimal time-varying hedge ratios. Applied Economics Letters, 14(7), 503–509. https://doi.org/10.1080/13504850500447331
   Web of Science ®Google Scholar
• Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 53(6), 1315–1335. https://doi.org/10.2307/1913210
   Web of Science ®Google Scholar
• Lee, S. B., & Kim, K. J. (1993). Does the October 1987 crash strengthen the co‐movements among national stock markets? Review of Financial Economics, 3(1), 89–102. https://doi.org/10.1002/j.1873-5924.1993.tb00574.x
   Google Scholar
• Leung, H., Schiereck, D., & Schroeder, F. (2017). Volatility spillovers and determinants of contagion: Exchange rate and equity markets during crises. Economic Modelling, 61, 169–180. https://doi.org/10.1016/j.econmod.2016.12.011
   Web of Science ®Google Scholar
• Lien, D., Lee, G., Yang, L., & Zhang, Y. (2018). Volatility spillovers among the US and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis. The North American Journal of Economics and Finance, 46, 187–201. https://doi.org/10.1016/j.najef.2018.04.006
   Web of Science ®Google Scholar
• Liu, L. (2014). Extreme downside risk spillover from the United States and Japan to Asia-Pacific stock markets. International Review of Financial Analysis, 33, 39–48. https://doi.org/10.1016/j.irfa.2013.07.009
   Web of Science ®Google Scholar
• Liu, T., & Gong, X. (2020). Analyzing time-varying volatility spillovers between the crude oil markets using a new method. Energy Economics, 87, 104711. https://doi.org/10.1016/j.eneco.2020.104711
   Web of Science ®Google Scholar
• Liu, K., Luo, C., & Li, Z. (2019). Investigating the risk spillover from crude oil market to BRICS stock markets based on Copula-POT-CoVaR models. Quantitative Finance and Economics, 3(4), 754–771. https://doi.org/10.3934/QFE.2019.4.754
   Web of Science ®Google Scholar
• Liu, Z., Tseng, H. K., Wu, J. S., & Ding, Z. (2020). Implied volatility relationships between crude oil and the US stock markets: Dynamic correlation and spillover effects. Resources Policy, 66, 101637. https://doi.org/10.1016/j.resourpol.2020.101637
   Web of Science ®Google Scholar
• Longin, F., & Solnik, B. (1995). Is the correlation in international equity returns constant: 1960–1990? Journal of International Money and Finance, 14(1), 3–26. https://doi.org/10.1016/0261-5606(94)00001-H
   Web of Science ®Google Scholar
• Majid, M., Meera, A., & Omar, M. (2008). Interdependence of ASEAN-5 stock markets from the US and Japan. Global Economic Review, 37(2), 201–225. https://doi.org/10.1080/12265080802021201
   Web of Science ®Google Scholar
• Markowitz, H. (1952). The utility of wealth. Journal of Political Economy, 60(2), 151–158. https://doi.org/10.1086/257177
   Web of Science ®Google Scholar
• Mathur, I., & Subrahmanyam, V. (1990). Interdependencies among the Nordic and US stock markets. The Scandinavian Journal of Economics, 92(4), 587–597. https://doi.org/10.2307/3440394
   Web of Science ®Google Scholar
• Melvin, M. (2003). A stock market boom during a financial crisis?: ADRs and capital outflows in Argentina. Economics Letters, 81(1), 129–136. https://doi.org/10.1016/S0165-1765(03)00156-3
   Web of Science ®Google Scholar
• Mensi, W., Beljid, M., Boubaker, A., & Managi, S. (2013). Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold. Economic Modelling, 32, 15–22. https://doi.org/10.1016/j.econmod.2013.01.023
   Web of Science ®Google Scholar
• Mensi, W., Maitra, D., Vo, X. V., & Kang, S. H. (2021). Asymmetric volatility connectedness among main international stock markets: A high frequency analysis. Borsa Istanbul Review, 21(3), 291–306. https://doi.org/10.1016/j.bir.2020.12.003
   Web of Science ®Google Scholar
• Milunovich, G., & Thorp, S. (2006). Valuing volatility spillovers. Global Finance Journal, 17(1), 1–22. https://doi.org/10.1016/j.gfj.2006.06.007
   Google Scholar
• Panda, A. K., & Nanda, S. (2018). Time-varying synchronization and dynamic conditional correlation among the stock market returns of leading South American economies. International Journal of Managerial Finance, 14(2), 245–262. https://doi.org/10.1108/IJMF-11–2016-0206
   Web of Science ®Google Scholar
• Panda, P., Vasudevan, S., & Panda, B. (2021). Dynamic Connectedness among BRICS and major Countries Stock Markets. Journal of Public Affairs, 21(3), e2265. https://doi.org/10.1002/pa.2265
   Web of Science ®Google Scholar
• Pesaran, M. H., & Pick, A. (2007). Econometric issues in the analysis of contagion. Journal of Economic Dynamics and Control, 31(4), 1245–1277. https://doi.org/10.1016/j.jedc.2006.03.008
   Web of Science ®Google Scholar
• Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
   Web of Science ®Google Scholar
• Reinhart, C., & Calvo, S. G. (1996). Capital flows to Latin America: Is there evidence of contagion effects? Munich Personal RePEc Archive. https://mpra.ub.uni-muenchen.de/7124/
   Google Scholar
• Ross, S. A. (1989). Information and volatility: The no‐arbitrage martingale approach to timing and resolution irrelevancy. The Journal of Finance, 44(1), 1–17.
   Web of Science ®Google Scholar
• Saleem, K., & Vaihekoski, M. (2008). Pricing of global and local sources of risk in Russian stock market. Emerging Markets Review, 9(1), 40–56. https://doi.org/10.1016/j.ememar.2007.08.002
   Google Scholar
• Samitas, A., Kampouris, E., & Polyzos, S. (2022). Covid-19 pandemic and spillover effects in stock markets: A financial network approach. International Review of Financial Analysis, 80, 102005. https://doi.org/10.1016/j.irfa.2021.102005
   PubMed Web of Science ®Google Scholar
• Sensoy, A., Hacihasanoglu, E., & Nguyen, D. K. (2015). Dynamic convergence of commodity futures: Not all types of commodities are alike. Resources Policy, 44, 150–160. https://doi.org/10.1016/j.resourpol.2015.03.001
   Web of Science ®Google Scholar
• Srivastava, S., Lin, H., Premachandra, I. M., & Roberts, H. (2016). Global risk spillover and the predictability of sovereign CDS spread: International evidence. International Review of Economics & Finance, 41, 371–390. https://doi.org/10.1016/j.iref.2015.10.047
   Web of Science ®Google Scholar
• Strohsal, T., & Weber, E. (2015). Time-varying international stock market interaction and the identification of volatility signals. Journal of Banking & Finance, 56, 28–36. https://doi.org/10.1016/j.jbankfin.2015.01.020
   Web of Science ®Google Scholar
• Su, X. (2020). Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis. The North American Journal of Economics and Finance, 51, 101098. https://doi.org/10.1016/j.najef.2019.101098
   Web of Science ®Google Scholar
• Tauchen, G. E., & Pitts, M. (1983). The price variability-volume relationship on speculative markets. Econometrica: Journal of the Econometric Society, 51(2), 485–505. https://doi.org/10.2307/1912002
   Web of Science ®Google Scholar
• Thomas, N. M., Kashiramka, S., & Yadav, S. S. (2017). Dynamic linkages among developed, emerging and frontier capital markets of Asia-Pacific region. Journal of Advances in Management Research, 14(3), 332–351. https://doi.org/10.1108/JAMR-10-2016-0088
   Google Scholar
• Trihadmini, N., & Falianty, T. A. (2020). Stock market contagion and spillover effects of the global financial crisis on five ASEAN countries. Institutions and Economies.
   Google Scholar
• Trung, N. B. (2019). The spillover effects of US economic policy uncertainty on the global economy: A global VAR approach. The North American Journal of Economics and Finance, 48, 90–110. https://doi.org/10.1016/j.najef.2019.01.017
   Web of Science ®Google Scholar
• Uludag, B. K., & 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
   Web of Science ®Google Scholar
• Urquhart, A., & Zhang, H. (2019). Is Bitcoin a hedge or safe haven for currencies? An intraday analysis. International Review of Financial Analysis, 63, 49–57. https://doi.org/10.1016/j.irfa.2019.02.009
   Web of Science ®Google Scholar
• Wang, Y., & Liu, L. (2016). Spillover effect in Asian financial markets: A VAR-structural GARCH analysis. China Finance Review International.
   Google Scholar
• Wang, G. J., Xie, C., Jiang, Z. Q., & Stanley, H. E. (2016). Extreme risk spillover effects in world gold markets and the global financial crisis. International Review of Economics & Finance, 46, 55–77. https://doi.org/10.1016/j.iref.2016.08.004
   Web of Science ®Google Scholar
• Xiao, Y. (2020). The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach. International Review of Economics & Finance, 65, 173–186. https://doi.org/10.1016/j.iref.2019.10.009
   Web of Science ®Google Scholar
• Yarovaya, L., Brzeszczyński, J., & Lau, C. K. M. (2017). Asymmetry in spillover effects: Evidence for international stock index futures markets. International Review of Financial Analysis, 53, 94–111. https://doi.org/10.1016/j.irfa.2017.07.007
   Web of Science ®Google Scholar
• Yasir, M., & Önder, A. Ö. (2022). Time-varying herding spillover for emerging countries: Evidence from BRIC countries and Turkey. Review of Behavioral Finance (ahead-of-print). https://doi.org/10.1108/RBF-10-2021-0218
   Google Scholar
• Yilmaz, K. (2010). Return and volatility spillovers among the East Asian equity markets. Journal of Asian Economics, 21(3), 304–313. https://doi.org/10.1016/j.asieco.2009.09.001
   Google Scholar
• Zhang, H., & Giouvris, E. (2022). Measures of Volatility, Crises, Sentiment and the Role of US’ Fear’Index (VIX) on Herding in BRICS (2007–2021). Journal of Risk and Financial Management, 15(3), 134. https://doi.org/10.3390/jrfm15030134
   Web of Science ®Google Scholar
• Zhang, W., Zhuang, X., & Wu, D. (2020). Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis. Finance Research Letters, 34, 101274. https://doi.org/10.1016/j.frl.2019.08.022
   Web of Science ®Google Scholar
• Zhong, Y., & Liu, J. (2021). Correlations and volatility spillovers between China and Southeast Asian stock markets. The Quarterly Review of Economics and Finance, 81, 57–69. https://doi.org/10.1016/j.qref.2021.04.001
   Web of Science ®Google Scholar