پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شمارهها | 6,573 |
| تعداد مقالات | 71,037 |
| تعداد مشاهده مقاله | 125,522,676 |
| تعداد دریافت فایل اصل مقاله | 98,782,380 |
Stock Markets and Exchange Rates throughout the COVID-19 Pandemic: Other Evidences for Italy and China Case | ||
| Iranian Economic Review | ||
| مقاله 14، دوره 28، شماره 4، اسفند 2024، صفحه 1425-1447 اصل مقاله (901.34 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ier.2024.353353.1007609 | ||
| نویسندگان | ||
| Rym Regaïeg* 1؛ Amal Jmaii2؛ Nidhal Mgadmi3 | ||
| 1SEPAL ISG Tunis Lab., Higher Institute of Management of Tunis, University of Tunis, Tunis, Tunisia. | ||
| 2LAREQUAD Lab., Faculty of Economics and Management of Tunis, University of Tunis El Manar (UTM), Tunis, Tunisia. | ||
| 3THEMA Lab., Faculty of Economics and Management of Mahdia, University of Monastir, Monastir, Tunisia. | ||
| چکیده | ||
| This paper examines the impact of change in COVID-19 cases/deaths on stock market and exchange rate using daily data covering the period between 31 December 2019 and 12 March 2020, of Italy and China. Founded on the Markov Regime Switching model, we identified two stress regimes: normal stress regime and high stress regime. Threshold VAR Model is used to differentiate the exchange rate and stock market prices dynamics between normal stress regime and high stress regime. We found that of COVID-19 pandemic have no/weakly impact on Chinese and Italian national currencies but can negatively influence stock market prices. The contribution of this framework is the setting of an estimated threshold value of number of death/cases COVID-19 above it we consider a high stress period. These findings are very important for policymakers in order to predict sanitary pandemic effects such as COVID-19 on the global markets and help in policies perception of fighting against any sanitary pandemic. | ||
| کلیدواژهها | ||
| Markov Switching؛ Sanitary Disease؛ Stock Market Prices؛ Stress Period؛ TVAR Model | ||
| مراجع | ||
|
Ashraf, B. N. (2020). Stock Markets’ Reaction to COVID-19: Cases or Fatalities? Research in International Business and Finance, 54, 1-7.
Andrews, D. W., & Ploberger, W. (1994). Optimal Tests when a Nuisance Parameter is Present Only under the Alternative. Econometrica: Journal of the Econometric Society, 62(6), 1383-1414.
Balke, N. S. (2000). Credit and Economic Activity: Credit Regimes and Nonlinear Propagation of Shocks. The Review of Economics and Statistics, 82(2), 344-349.
Baker, S. R., Bloom, N., Davis, S. J., Kost, K. J., Sammon, M. C., & Viratyosin, T. (2020). The Unprecedented Stock Market Impact of COVID-19. National Bureau of Economic Research, Working Paper, 26945, 1-24.
Chatterjee, S., Chiu, C. W., Duprey, T., & Hacıoğlu‐Hoke, S. (2021). Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom. Oxford Bulletin of Economics and Statistics, 84(2), 380-400.
Calza, A. & Sousa, J. (2006). Output and Inflation Responses to Credit Shocks: Are There Threshold Effects in the Euro Area? Studies in Nonlinear Dynamics & Econometrics, 10(2), Retrieved from https://www.degruyter.com/document/doi/10.2202/1558-3708.1253/pdf
Chen, H. C., & Yeh, C. W. (2021). Global Financial Crisis and COVID-19: Industrial Reactions. Finance Research Letters, 42, 1-13.
Devpura, N. (2021). Effect of COVID-19 on the Relationship between Euro/USD Exchange Rate and Oil Price. MethodsX, 8, 1-8.
Evgenidis, A., & Tsagkanos, A. (2017). Asymmetric Effects of the International Transmission of US Financial Stress. A Threshold-VAR Approach. International Review of Financial Analysis, 51, 69-81.
Foroni, C., Marcellino, M., & Stevanovic, D. (2020). Forecasting the Covid-19 Recession and Recovery: Lessons from the Financial Crisis. International Journal of Forecasting, 38(2), 596-612.
Goodell, J. W. (2020). COVID-19 and Finance: Agendas for Future Research. Finance Research Letters, 35, 1-5.
Gunay, S. (2020). A New Form of Financial Contagion: COVID-19 and Stock Market Responses. SSRN, 3584243, 1-19.
Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
Hansen, B. E. (1999). Threshold Effects in Non-Dynamic Panels: Estimation, Testing, and Inference. Journal of Econometrics, 93(2), 345-368.
Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603.
Hubrich, K., & Teräsvirta, T. (2013). Thresholds and Smooth Transitions in Vector Autoregressive Models. In VAR Models in Macroeconomics–New Developments and Applications: Essays in Honor of Christopher A. Sims (32, 273-326). Leeds: Emerald Group Publishing Limited.
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), 2800.
Liu, L., & Wan, J. (2011). A Study of Correlations between Crude Oil Spot and Futures Markets: A Rolling Sample Test. Physica A: Statistical Mechanics and its Applications, 390(21-22), 3754-3766.
He, Q., Liu, J., Wang, S., & Yu, J. (2020). The Impact of COVID-19 on Stock Markets. Economic and Political Studies, 8(3), 275-288.
Rahman, M. L., Amin, A., & Al Mamun, M. A. (2021). The COVID-19 Outbreak and Stock Market Reactions: Evidence from Australia. Finance Research Letters, 38, 1-7.
Rangel, J. G., & Engle, R. F. (2012). The Factor–Spline–GARCH Model for High and Low Frequency Correlations. Journal of Business & Economic Statistics, 30(1), 109-124.
Szczygielski, J. J., Bwanya, P. R., Charteris, A., & Brzeszczyński, J. (2021). The Only Certainty is Uncertainty: An Analysis of the Impact of COVID-19 Uncertainty on Regional Stock Markets. Finance Research Letters, 43, 101945.
Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202.
Wang, Y., Wei, Y., & Wu, C. (2010). Cross-Correlations between Chinese A-share and B-share Markets. Physica A: Statistical Mechanics and its Applications, 389(23), 5468-5478.
Xu, L. (2021). Stock Return and the COVID-19 Pandemic: Evidence from Canada and the US. Finance Research Letters, 38, 101872.
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. | ||
|
آمار تعداد مشاهده مقاله: 23 تعداد دریافت فایل اصل مقاله: 17 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب