Browse > Article
http://dx.doi.org/10.13106/jafeb.2021.vol8.no2.0747

Linkage between US Financial Uncertainty and Stock Markets of SAARC Countries  

AZIZ, Tariq (Sukkur IBA University)
MARWAT, Jahanzeb (Sukkur IBA University)
MUSTAFA, Sheraz (Sukkur IBA University)
ZEESHAN, Asma (Fast University)
IQBAL, Yasir (University of Canberra)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.2, 2021 , pp. 747-757 More about this Journal
Abstract
The primary purpose of the study is to investigate the volatility spillover from financial uncertainty (FU) of the United States (US) to the stock markets of SAARC member countries including India, Sri-Lanka, Pakistan, and Bangladesh. The empirical literature overlooked SAARC countries and the FU index. Based on the estimation method, the data of FU is available for three different forecast horizons including 1-month, 3-months, and 12-months. For empirical analysis, monthly data is used from February 2013 to September 2019. EGARCH model is employed to investigate the volatility spillover effects. The findings of the study show that the spillover effect of FU varies with the forecast horizon. The FU with a higher forecast horizon has a significant spillover effect on more countries. The spillover effect of US financial uncertainty is negative in most of the SAARC countries. Bangladesh stock market is influenced by FU with all three forecast horizons whereas the volatility of the Pakistan stock market is not influenced by FU with any forecast horizon. The findings are consistent with the concept of "limited trade openness" in the financial markets of emerging economies. The emerging economies avoid financial market openness to minimize the risk of spillover of other countries.
Keywords
Financial Uncertainty; SAARC; EGARCH; Stock Returns; Spillover;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Aramonte, S. (2014). Macroeconomic uncertainty and the crosssection of option returns. Journal of Financial Markets, 21, 25-49. https://doi.org/10.1016/j.finmar.2014.06.001   DOI
2 Adjasi, C. K. (2009). Macroeconomic uncertainty and conditional stock‐price volatility in frontier African markets. The Journal of Risk Finance, 10(4), 333-349. https://doi.org/10.1108/15265940910980641.   DOI
3 Alexander, C., & Lazar, E. (2006). Normal mixture GARCH (1, 1): Applications to exchange rate modeling. Journal of Applied Econometrics, 21(3), 307-336. https://doi.org/10.1002/jae.849   DOI
4 Arouri, M., Estay, C., Rault, C., & Roubaud, D. (2016). Economic policy uncertainty and stock markets: Long-run evidence from the US. Finance Research Letters, 18, 136-141. https://doi.org/10.1016/j.frl.2016.04.011   DOI
5 Asgharian, H., Christiansen, C., & Hou, A. J. (2015). Effects of macroeconomic uncertainty on the stock and bond markets. Finance Research Letters, 13, 10-16. https://doi.org/10.1016/j.frl.2015.03.008   DOI
6 Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636. https://doi.org/10.1093/qje/qjw024   DOI
7 Bali, T. G., Brown, S. J., & Caglayan, M. O. (2014). Macroeconomic risk and hedge fund returns. Journal of Financial Economics, 114(1), 1-19. https://doi.org/10.1016/j.jfineco.2014.06.008   DOI
8 Bali, T. G., Brown, S. J., & Tang, Y. (2015). Macroeconomic uncertainty and expected stock returns (Research Paper 2407279). Georgetown McDonough School of Business. https://doi.org/10.2139/SSRN.2407279   DOI
9 Barberis, N., Shleifer, A., & Wurgler, J. (2005). Comovement. Journal of Financial Economics, 75(2), 283-317. https://doi.org/10.1016/j.jfineco.2004.04.003   DOI
10 Beber, A., & Brandt, M. W. (2009). Resolving macroeconomic uncertainty in stock and bond markets. Review of Finance, 13(1), 1-45. https://doi.org/10.1093/rof/rfn025   DOI
11 Bekaert, G., & Engstrom, E. (2017). Asset return dynamics under habits and the bad environment-good environment fundamentals. Journal of Political Economy, 125(3), 713-760. http://dx.doi.org/10.1086/691450   DOI
12 Bekaert, G., Engstrom, E., & Ermolov, A. (2015). Bad environments, good environments: A non-Gaussian asymmetric volatility model. Journal of Econometrics, 186(1), 258-275. https://doi.org/10.1016/j.jeconom.2014.06.021   DOI
13 Bekaert, G., & Harvey, C. R. (2005). Market integration and contagion. The Journal of Business, 78(1), 39-70. http://doi.org/10.1086/426519   DOI
14 Bhar, R. (2001). Return and volatility dynamics in the spot and futures markets in Australia: An intervention analysis in a bivariate EGARCH‐X framework. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 21(9), 833-850. https://doi.org/10.1002/fut.1903   DOI
15 Brooks, C. (2019). Introductory econometrics for finance. London, UK: Cambridge University Press.
16 Bhar, R., & Nikolova, B. (2009). Return, volatility spillovers, and dynamic correlation in the BRIC equity markets: An analysis using a bivariate EGARCH framework. Global Finance Journal, 19(3), 203-218. https://doi.org/10.1016/j.gfj.2008.09.005   DOI
17 Bhattarai, S., Chatterjee, A., & Park, W. Y. (2019). Global spillover effects of US uncertainty (Working Paper No. 107). Institute of Economic Research Seoul National University. https://ier.snu.ac.kr/activity/working-papers?md=download&seqidx=7
18 Boubaker, S., Jouini, J., & Lahiani, A. (2016). Financial contagion between the US and selected developed and emerging countries: The case of the subprime crisis. The Quarterly Review of Economics and Finance, 61, 14-28. https://doi.org/10.1016/j.qref.2015.11.001   DOI
19 Campbell, J. Y. (1993). Intertemporal asset pricing without consumption data. American Economic Review, 83(3), 487-512. https://www.jstor.org/stable/2117530
20 Campbell, J. Y. (1996). Understanding risk and return. The Journal of Political Economy, 104(2), 298-345. https://www.jstor.org/stable/2138928   DOI
21 Chen, H. (2010). Macroeconomic conditions and the puzzles of credit spreads and capital structure. The Journal of Finance, 65(6), 2171-2212. https://doi.org/10.1111/j.1540-6261.2010.01613.x   DOI
22 Chiang, T. C. (2019). An empirical analysis of economic policy uncertainty and stock returns in Asian markets. Research in International Business and Finance, 47, 264-278. https://doi.org/10.1108/S2514-465020190000007004   DOI
23 Donadelli, M. (2015). Asian stock markets, US economic policy uncertainty, and US macro-shocks. New Zealand Economic Papers, 49(2), 103-133. https://doi.org/10.1080/00779954.2014.890024   DOI
24 Chinzara, Z. (2011). Macroeconomic uncertainty and conditional stock market volatility in South Africa. South African Journal of Economics, 79(1), 27-49. https://doi.org/10.1111/j.1813-6982.2011.01262.x   DOI
25 Dakhlaoui, I., & Aloui, C. (2016). The interactive relationship between the US economic policy uncertainty and BRIC stock markets. International Economics, 146, 141-157. https://doi.org/10.1016/j.inteco.2015.12.002   DOI
26 Demir, E., & Ersan, O. (2018). The impact of economic policy uncertainty on stock returns of Turkish tourism companies. Current Issues in Tourism, 21(8), 847-855. https://doi.org/10.1080/13683500.2016.1217195   DOI
27 Du, D. N., & Minh, C. P. (2018). Search-based sentiment and stock market reactions: An empirical evidence in Vietnam. The Journal of Asian Finance, Economics, and Business, 5(4), 45-56. https://doi.org/10.13106/jafeb.2018.vol5.no4.45   DOI
28 Fang, L., Qian, Y., Chen, Y., & Yu, H. (2018). How does stock market volatility react to NVIX? Evidence from developed countries. Physica A: Statistical Mechanics and its Applications, 505, 490-499. https/://doi.org/10.1016/j.physa.2018.03.039   DOI
29 Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: Measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261. https://doi.org/10.1111/0022-1082.00494   DOI
30 Guo, P., Zhu, H., & You, W. (2018). Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: A quantile regression approach. Finance Research Letters, 25, 251-258. https://doi.org/10.1016/j.frl.2017.11.001   DOI
31 Kannadhasan, M., & Das, D. (2019). Do Asian emerging stock markets react to international economic policy uncertainty and geopolitical risk alike? A quantile regression approach. Finance Research Letters, 34(C), 101276. https://doi.org/10.1016/j.frl.2019.08.024.   DOI
32 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://www.jstor.org/stable/2962024   DOI
33 Han, L., Liu, Y., & Yin, L. (2019). Uncertainty and currency performance: A quantile-on-quantile approach. The North American Journal of Economics and Finance, 48, 702-729. https://doi.org/10.1016/j.najef.2018.08.006   DOI
34 Jurado, K., Ludvigson, S. C., & Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216. https://doi.org/10.1257/aer.20131193   DOI
35 Karamat, K., Huawei, Z., Han, Z., Huilin, Y., Muhammad Haroon, S., & Atif, J. (2020). The impact of COVID-19 pandemic on stock markets: An empirical analysis of world major stock indices. The Journal of Asian Finance, Economics, and Business, 7(7), 463-474. htttps://doi.org/10.13106/jafeb.2020.vol7.no7.463   DOI
36 Li, X. I., Balcilar, M., Gupta, R., & Chang, T. (2016). The causal relationship between economic policy uncertainty and stock returns in China and India: Evidence from a bootstrap rolling window approach. Emerging Markets Finance and Trade, 52(3), 674-689. https://doi.org/10.1080/1540496X.2014.998564   DOI
37 Liu, L. X., & Zhang, T. (2015). Economic policy uncertainty and stock market volatility. Finance Research Letters, 15, 99-105. https://doi.org/10.1016/j.frl.2015.08.009   DOI
38 Liu, L. X., & Zhang, L. (2008). Momentum profits, factor pricing, and macroeconomic risk. The Review of Financial Studies, 21(6), 2417-2448. https://doi.org/10.1093/rfs/hhn090   DOI
39 Luo, Y., & Zhang, C. (2020). Economic policy uncertainty and stock price crash risk. Research in International Business and Finance, 51, 101112. https://doi.org/10.1016/j.ribaf.2019.101112   DOI
40 Ludvigson, S. C., Ma, S., & Ng, S. (2015). Uncertainty and business cycles: Exogenous impulse or endogenous response? (Working Paper 21803) National Bureau of Economic Research. http://www.columbia.edu/-sn2294/papers/lmn1.pdf
41 Manela, A., & Moreira, A. (2017). News implied volatility and disaster concerns. Journal of Financial Economics, 123(1), 137-162. https://doi.org/10.1016/j.jfineco.2016.01.032   DOI
42 McIver, R. P., & Kang, S. H. (2020). Financial crises and the dynamics of the spillovers between the US and BRICS stock markets. Research in International Business and Finance, 54(C), 101276. https://doi.org/10.1016/j.ribaf.2020.101276   DOI
43 Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867-887. https://doi.org/10.2307/1913811   DOI
44 Mo, B., Mu, J., & Zhang, B. (2019). The relationship between news-based implied volatility and volatility of the US stock market: What can we learn from the multiscale perspective? Physica A: Statistical Mechanics and its Applications, 526, 121003. https://doi.org/10.1016/j.physa.2019.04.239   DOI
45 Mustika, R., Nurul, A., Aminullah, A. M., Thuba, J., & Mahfuzur, R. (2016). Risk volatility measurement: Evidence from Indonesian stock market. The Journal of Asian Finance, Economics, and Business, 3(3), 57-65. https://doi.org/10.13106/jafeb.2016.vol3.no3.57.   DOI
46 Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370. https://doi.org/10.2307/2938260   DOI
47 Sharma, G. D., & Bodla, B. S (2011). Inter‐linkages among stock markets of South Asia. Asia Pacific Journal of Business Administration, 3(2), 132-148. https://doi.org/10.1108/17574321111169821   DOI
48 Ozturk, E. O., & Sheng, X. S. (2018). Measuring global and countryspecific uncertainty. Journal of International Money and Finance, 88, 276-295. https://doi.org/10.1016/j.jimonfin.2017.07.014   DOI
49 Phan, D. H. B., Sharma, S. S., & Tran, V. T. (2018). Can economic policy uncertainty predict stock returns? Global evidence. Journal of International Financial Markets, Institutions, and Money, 55, 134-150. https://doi.org/10.1016/j.intfin.2018.04.004   DOI
50 Pukthuanthong, K., & Roll, R. (2009). Global market integration: An alternative measure and its application. Journal of Financial Economics, 94(2), 214-232. https://doi.org/10.1016/j.jfineco.2008.12.004   DOI
51 Su, Z., Fang, T., & Yin, L. (2017). The role of news-based implied volatility among US financial markets. Economics Letters, 157, 24-27. https://doi.org/10.1016/j.econlet.2017.05.028   DOI
52 Su, Z., Fang, T., & Yin, L. (2018). Does NVIX matter for market volatility? Evidence from Asia-Pacific markets. Physica A: Statistical Mechanics and its Applications, 492, 506-516. https://doi.org/10.1016/j.physa.2017.10.025   DOI
53 Su, Z., Fang, T., & Yin, L. (2019). Understanding stock market volatility: What is the role of US uncertainty? The North American Journal of Economics and Finance, 48, 582-590. https://doi.org/10.1016/j.najef.2018.07.014   DOI
54 Su, Z., Lu, M., & Yin, L. (2019). Chinese stock returns and the role of news-based uncertainty. Emerging Markets Finance and Trade, 55(13), 2949-2969. https://doi.org/10.1080/1540496X.2018.1562898   DOI
55 Trung, N. B. (2019). The spillover effect of the US uncertainty on emerging economies: A panel VAR approach. Applied Economics Letters, 26(3), 210-216. https://doi.org/10.1080/13504851.2018.1458183   DOI