Document Type : Original Research


1 Faculty of Accounting and Finance, Nha Trang University, Nha Trang city, Vietnam

2 Faculty of Business, Greenwich Vietnam, FPT University, Danang Campus, Da Nang, Vietnam


This study empirically investigated the existence of Calendar effects by using closing daily data for the Vietnam index (VN-index) before and during the Covid-19 pandemic. Daily returns of the VN-Index from 2 January 2018 to 12 August 2022 are used in this study to ascertain calendar anomalies in Ho Chi Minh Stock Exchange (HOSE). To test these effects, the entire study period is divided into two sub-periods: during and before the Covid-19 crisis. Then, the ordinary least square (OLS) method and the Generalized Autoregressive Conditional Heteroskedasticity [GARCH (1,1)] regression model were employed. The empirical results from the OLS model support the occurrence of calendar anomalies for the HOSE both before and during the Covid-19 pandemic while the results of GARCH (1,1) only confirmed the positively significant effect on Friday during the Covid-19 periods. Regarding stock returns, positive returns were found only on Friday, during the Covid-19 pandemic. It implies that Covid-19 has changed the nature of the stock market from efficient to inefficient. The study’s findings suggest that the Covid-19 crisis significantly impacted the daily returns anomaly in Vietnam’s HOSE.


Main Subjects


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Ahmar, A. S., & del Val, E. B. (2020). SutteARIMA: Short-term forecasting method, a case: Covid-19 and stock market in Spain. Science of the Total Environment, 729, 138883.
Al-Awadhi, A. M., Al-Saifi, K., Al-Awadhi, A., & Alhamadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of Behavioral and Experimental Finance, 27, 100326.
Alexakis, P., & Xanthakis, M. (1995). Day of the week effect on the Greek stock market. Applied Financial Economics5(1), 43-50.
Anh, D.L.T. and Gan, C. (2021), “The impact of the COVID-19 lockdown on stock market performance: evidence from Vietnam”, Journal of Economic Studies, Vol. 48 No. 4, pp. 836-851.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
Brooks, C. (2019). Introductory econometrics for finance: Cambridge university press.
Cabello, A., & Ortiz, E. (2003). Day of the week and month of the year anomalies in the Mexican stock market. Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), 2(3).
Chen, L., Li, S., & Lin, W. (2007). Corporate governance and corporate performance: Some evidence from newly listed firms on Chinese stock markets. International Journal of Accounting, Auditing and Performance Evaluation, 4(2), 183–197.
Chen, L., Qiao, Z., Wang, M., Wang, C., Du, R., & Stanley, H. E. (2018). Which artificial intelligence algorithm better predicts the Chinese stock market? IEEE Access, 6, 48625–48633.
Government of the Socialist Republic of Viet Nam [GOV] (2020). Decree No. 155/2020/ND-CP dated December 31, 2020 on elaboration of some Articles of the Law on Securities. Retrieved from
Dong Loc, T., Lanjouw, G., & Lensink, R. (2010). Stock-market efficiency in thin-trading markets: the case of the Vietnamese stock market. Applied Economics42(27), 3519-3532.
Engle, R. F. (1982). A general approach to Lagrange multiplier model diagnostics. Journal of Econometrics20(1), 83-104.
French, K. R. (1980). Stock Returns and the Weekend Effect. Journal of Financial Economics, 8(1), 55–69.
Gbeda, J. M., & Peprah, J. A. (2018). Day of the week effect and stock market volatility in Ghana and Nairobi stock exchanges. Journal of Economics and Finance42(4), 727-745.
Gibbons, M. R., & Hess, P. (1981). Day of the Week Effects and Asset Returns. The Journal of Business, 54(4), 579–596.
Gormsen, N. J., & Koijen, R. S. (2020). Coronavirus: Impact on stock prices and growth expectations. The Review of Asset Pricing Studies, 10(4), 574-597.
Haugen, R. A., & Jorion, P. (1996). The January effect: Still there after all these years. Financial Analysts Journal52(1), 27-31.
Hung, Dao Van, Nguyen Thi Minh Hue, and Vu Thuy Duong (2021). The Impact of COVID-19 on Stock Market Returns in Vietnam. Journal of Risk and Financial Management 14: 441.
Kok, S. C., & Geetha, C. (2023). A comparison of the weak-form efficiency of the Asean stock markets before and during the covid-19 pandemic. Malaysian Journal of Business and Economics (MJBE)10(1), 1-7.
Kristjanpoller, W. (2012a). Day of the Week Effect in Latin American Stock Markets. Revista de Análisis Económico, 27(1), 71–89.
Le Hau, L. (2010). Day-of-the-week effects in different stock markets: New evidence on model-dependency in testing seasonalities in stock returns (No. 09). Development and Policies Research Center (DEPOCEN), Vietnam.
Le, T. N., & Duong, B. T. (2022). Stock market reaction to credit rating changes: evidence from Vietnamese stock market. International Journal of Education, Business and Economics Research2(3), 1-13.
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.
Loc, T. D. (2006). Equitisation and stock-market development: The case of Vietnam. University of Groningen.
Luu, C.T., Pham, C.H., Pham, L. (2016), Seasonality effect on the Vietnamese stock exchange. International Journal of Financial Research, 7(3), 28-4
Nguyen, C. T., Hai, P. T., & Nguyen, H. K. (2021). Stock market returns and liquidity during the COVID-19 outbreak: evidence from the financial services sector in Vietnam. Asian Journal of Economics and Banking.
Paital, R. R., & Panda, A. K. (2018). Day of the week and weekend effects in the Indian stock market. Theoretical Economics Letters, 8(11), 2559–2568.
Phan Tran Trung, D., & Pham Quang, H. (2019). Adaptive market hypothesis: Evidence from the Vietnamese stock market. Journal of Risk and Financial Management, 12(2), 81.
Phan, K. C., & Zhou, J. (2014). Market efficiency in emerging stock markets: A case study of the Vietnamese stock market. IOSR Journal of Business and Management16(4), 61-73.
Plastun, A., Sibande, X., Gupta, R., & Wohar, M. E. (2019). Rise and Fall of Calendar Anomalies Over a Century. North American Journal of Economics and Finance, 49, 181–205.
Sahoo, M. (2021). COVID‐19 impact on stock market: Evidence from the Indian stock market. Journal of Public Affairs, 21(4), e2621.
Seif, M., Docherty, P., & Shamsuddin, A. (2017). Seasonal anomalies in advanced emerging stock markets. The Quarterly Review of Economics and Finance66, 169-181.
Shaik, M., & Maheswaran, S. (2017). Market efficiency of ASEAN stock markets. Asian Economic and Financial Review7(2), 109.
Sharma, S. (2011). Day of week effect: Evidences from indian stock market. Indian Journal of Commerce and Management Studies, 2(6), 25-30.
Tadepalli, M. S., & Jain, R. K. (2018). The Day-of-the-Week (DOW) Effect on Stock Markets in India: Insights and Perspectives on a Seasonal Anomaly. New Zealand Journal of Applied Business Research, 16(2), 41–70.
Truong, L. D., & Friday, H. S. (2021). The impact of the introduction of index futures on the daily returns anomaly in the Ho Chi Minh Stock Exchange. International Journal of Financial Studies, 9(3), 43.
Vo, X. V., & Truong, Q. B. (2018). Does momentum work? Evidence from Vietnam stock market. Journal of Behavioral and Experimental Finance17, 10-15.
Winkelried, D., & Iberico, L. A. (2018). Calendar Effects in Latin American Stock Markets. Empirical Economics, 54(3), 1215–1235.
Zhang, J., Lai, Y., & Lin, J. (2017). The Day-of-the-Week Effects of Stock Markets in Different Countries. Finance Research Letters, 20(February), 47–62.
Zhang, S. X., Huang, H., & Wei, F. (2020). Geographical distance to the epicenter of Covid-19 predicts the burnout of the working population: Ripple effect or typhoon eye effect? Psychiatry Research, 112998.288.