Testing volatility spillovers using GARCH models in the Japanese stock market during COVID-19
-
Author(s)Cristi SpulbarLink to ORCID Index: https://orcid.org/0000-0002-3909-9496
,
Ramona BirauLink to ORCID Index: https://orcid.org/0000-0003-1638-4291
,
Jatin TrivediLink to ORCID Index: https://orcid.org/0000-0003-4418-8124
,
Iqbal Thonse HawaldarLink to ORCID Index: https://orcid.org/0000-0001-7181-2493
,
Elena Loredana MineaLink to ORCID Index: https://orcid.org/0000-0002-9656-6812
-
DOIhttp://dx.doi.org/10.21511/imfi.19(1).2022.20
-
Article InfoVolume 19 2022, Issue #1, pp. 262-273
- Cited by
- 988 Views
-
307 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This paper investigates volatility spillovers in the stock market in Japan during the COVID-19 pandemic by using GARCH family models. The empirical analysis is focused on the dynamics of the NIKKEI 225 stock market index during the sample period from July 30, 1998, to January 24, 2022. In other words, the sample period covers both the period of the global financial crisis (GFC) and the COVID-19 pandemic. The econometrics includes GARCH (1,1), GJR (1,1), and EGARCH (1,1) models. By applying GARCH family models, this empirical study also examines the long-term behavior of the Japanese stock market.
The Japanese stock market is much more stable and efficient than emerging or frontier markets characterized by higher volatility and lower liquidity. The paper establishes that NIKKEI 225 index dynamics is different in intensity in the case of the two most recent extreme events analyzed, namely the global financial crisis (GFC)of 2007–2008 and the COVID-19 pandemic. The findings confirmed the presence of the leverage effect during the sample period. Moreover, the empirical results identified the presence of high volatility in the sample returns of the selected stock market. Nevertheless, the econometric framework showed that the negative implications of the GFC were much more severe and caused more significant contractions compared to the COVID-19 pandemic for the Japanese stock market. This study contributes to the existing literature by providing additional empirical evidence on the long-term behavior of the stock market in Japan, especially in the context of extreme events.
- Keywords
-
JEL Classification (Paper profile tab)G01, G15, G17
-
References43
-
Tables3
-
Figures4
-
- Figure 1. The trend of the NIKKEI 225 index using daily closing prices during the sample period
- Figure 2. The log-returns of the NIKKEI 225 index using daily closing prices during the sample period
- Figure 3. Evidence on autocorrelation and partial autocorrelation tested for NIKKEI 225 index during the sample period
- Figure 4. Relative frequency distribution for NIKKEI 225 index during the sample period
-
- Table 1. Frequency distribution for NIKKEI 225 index
- Table 2. Summary statistics
- Table 3. Statistical property of GARCH (1, 1), GJR (1, 1), and EGARCH (1, 1) models
-
- Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry-level analysis. Finance Research Letters, 37, 101748.
- Birau, R., Spulbar, C., Trivedi, J., & Florescu, I. (2021). Modeling volatility in the stock markets of Spain and Hong Kong using GARCH family models in the context of COVID-19 pandemic. Revista de Științe Politics. Revue des Sciences Politiques, 72, 13-21.
- Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
- Du, W. (2021). News and Market Efficiency in the Japanese Stock Market. Journal of Behavioral Finance, 22(3), 306-319.
- Duttilo, P., Gattone, S. A., & Di Battista, T. (2021). Volatility Modeling: An Overview of Equity Markets in the Euro Area during COVID-19 Pandemic. Mathematics, 9(11), 1212.
- Ejaz, A., Birau, R., Spulbar, C., Buda, R., & Tenea, A. C. (2020). The impact of domestic portfolio diversification strategies in Toronto stock exchange on Canadian textile manufacturing industry. Industria Textila, 71(3), 215-222.
- Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation. Econometrica, 50(4), 987-1007.
- FTSE Russell. (2021). FTSE Equity Country Classification, September 2021, Annual Announcement. FTSE Classification of Equity Markets.
- Gillani, D. Q., Gillani, S. A. S., Naeem, M. Z., Spulbar, C., Coker-Farrell, E., Ejaz, A., & Birau, R. (2021). The Nexus between Sustainable Economic Development and Government Health Expenditure in Asian Countries Based on Ecological Footprint Consumption. Sustainability, 13(12), 6824.
- Glosten, L., Jagannathan, R., & Runkle, D. (1993). On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801.
- Hamori, S. (2003). An Empirical Investigation of Stock Markets: The CCF Approach. New York: Kluwer Academic Publisher.
- Hamzaoui, N., & Regaieg, B. (2016). The Glosten-Jagannathan-Runkle-Generalized Autoregressive Conditional Heteroscedastic approach to investigating the foreign exchange forward premium volatility. International Journal of Economics and Financial Issues, 6(4), 1608-1615.
- Hawaldar, I. T. (2014). Seasonal analysis of abnormal returns after quarterly earnings announcements. International Journal of Accounting and Financial Reporting, 4(2), 501-519.
- Hawaldar, I. T. (2015). Empirical Testing of Capital Asset Pricing Model on Bahrain Bourse. Asian Journal of Finance & Accounting, 7(2), 107-119.
- Hawaldar, I. T. (2016). The Cross-Sectional Variations in Portfolio Returns: Evidence from Bahrain Bourse. British Journal of Economics, Finance and Management Sciences, 12(2), 1-11.
- Hawaldar, I. T., Birau, R., Spulbar, C., Rohit, B., Pinto, P., Rajesha, T. M., & Di Sciorio, F. (2020). Further evidence on the efficiency of Bahrain Bourse: A high challenge for other industries. Industria Textile, 71(5), 458-466.
- Hawaldar, I. T., Mallikarjunappa, T., & Nayak, P. (2007). Stock Price Adjustments to Quarterly Earnings Announcement: A Test of Semi-Strong Form of Efficiency. Gyan Management, 1(2), 25-42.
- Higashide, T., Tanaka, K., Kinkyo, T., & Hamori, S. (2021). New Dataset for Forecasting Realized Volatility: Is the Tokyo Stock Exchange Co-Location Dataset Helpful for Expansion of the Heterogeneous Autoregressive Model in the Japanese Stock Market? Journal of Risk and Financial Management, 14(5), 215.
- Kahraman, S., & Keser, M. (2022). Volatility Transmission Between the Japanese Stock Market and the Western Stock Market Indices: Time & Frequency Domain Connectedness Analysis with High-Frequency Data. Applied Economics, 54(6), 670-684.
- Kumar, A., Soni, R., Hawaldar, I. T., Vyas, M., & Yadav, V. (2020). The Testing of Efficient Market Hypotheses: A Study of Indian Pharmaceutical Industry. International Journal of Economics and Financial Issues, 10(3), 208- 216.
- Mazur, M., Dang, M., & Vega, M. (2021). COVID-19 and the March 2020 stock market crash. Evidence from S&P 1500. Finance Research Letters, 38, 101690.
- Meher, B. K., Hawaldar, I. T., Mohapatra, L., & Sarea, A. M. (2020a). The Impact of COVID-19 on Price Volatility of Crude Oil and Natural Gas Listed on Multi Commodity Exchange of India. International Journal of Energy Economics and Policy, 10(5), 422-431.
- Meher, B. K., Hawaldar, I. T., Mohapatra, L., Spulbar, C., & Birau, R. (2020b). The Effects of Environment, Society and Governance Scores on Investment Returns and Stock Market Volatility. International Journal of Energy Economics and Policy, 10(4), 234-239.
- Meher, B. K., Hawaldar, I. T., Spulbar, C. M., & Birau, F. R. (2021). Forecasting Stock Market Prices Using Mixed ARIMA Model: A Case Study of Indian Pharmaceutical Companies. Investment Management and Financial Innovations, 18(1), 42-54.
- Nelson, D. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347-370.
- Nguyen, M. K., & Le, D. N. (2021). Return Spillover from the US and Japanese Stock Markets to the Vietnamese Stock Market: A Frequency-Domain Approach. Emerging Markets Finance and Trade, 57(1), 47-58.
- Ohmura, H. (2022). The connection between stock market prices and political support: evidence from Japan. Applied Economics Letters, 29(1), 1-7.
- Palma-Ruiz, J. M., Castillo-Apraiz, J., & Gómez-Martínez, R. (2020). Socially Responsible Investing as a Competitive Strategy for Trading Companies in Times of Upheaval Amid COVID-19: Evidence from Spain. International Journal of Financial Studies, 8(3), 41.
- Poon, S. H., & Granger, C. W. J. (2003). Forecasting Volatility in Financial Markets: A Review. Journal of Economic Literature, 41(2), 478-539.
- Rabbani, M.R., Kayani, U., Bawazir, H.S., & Hawaldar, I. T. (2022). A Commentary on Emerging Markets Banking Sector Spillovers: Covid-19 Vs GFC Pattern Analysis. Heliyon, 8 (3), 1-8.
- Sajeev, K. C., Afjal, M., Spulbar, C., Birau, R., & Florescu, I. (2021). Evaluating the linkage between Behavioral Finance and Investment Decisions Amongst Indian Gen Z Investors Using Structural Equation Modeling. Revista de Științe Politice. Revue des Sciences Politiques, 72, 41-59.
- Sakamoto, S., & Sengoku, S. (2021). Predictability of Stock Price Fluctuations Based on Business Relationships: A Comparison of Normal and the COVID-19 Pandemic Periods in Japan. Sustainability, 13(18), 10146.
- Shen, J., & Shafiq, M. O. (2020). Short-term stock market price trend prediction using a comprehensive deep learning system. Journal of Big Data, 7, 66.
- Spulbar, C., & Birau, R. (2019). Emerging Research on Monetary Policy, Banking, and Financial Markets (322 p.). USA: IGI Global.
- Spulbar, C., Birau, R., Oluwi, V., Ejaz, A., Gorun, T. H., Calugăru, T., Zulfiqar, A. I., & Minea, E. L. (2021). Diversification opportunities in European stock markets and their impact on textile industry development based on a financial education approach. Industria Textila, 72(5), 528-537.
- Spulbar, C., Trivedi, J., & Birau, R. (2020). Investigating abnormal volatility transmission patterns between emerging and developed stock markets: a case study. Journal of Business Economics and Management, 21(6), 1561-1592.
- Spulbar, C., Trivedi, J., Birau, R., Tenea, C. A., & Ejaz, A. (2019). Estimating volatility spillovers, dynamic causal linkages, and international contagion patterns between developed stock markets: An empirical case study for USA, Canada, France, and UK. Annals of the “Constantin Brâncuşi” University of Târgu Jiu, Economy Series, 3, 44-62.
- Sultonov, M. (2020). The Impacts of International Political and Economic Events on Japanese Financial Markets. International Journal of Financial Studies, 8(3), 43.
- Takaishi, T. (2022). Time Evolution of Market Efficiency and Multifractality of the Japanese Stock Market. Journal of Risk and Financial Management, 15(1), 31.
- Trivedi, J., Spulbar, C., Birau, R., & Mehdiabadi, A. (2021a). Modelling volatility spillovers, cross-market correlation, and co-movements between stock markets in European Union: an empirical case study. Business, Management and Economics Engineering, 19(1), 70-90.
- Trivedi, J., Spulbar, C., Birau, R., & Minea, E. L. (2021b). Assessing the changes in the statistical property of selected stock markets behavior before and after COVID-19 pandemic: A case study. Research and Science Today, 22(2), 63-72.
- Watanabe, T. (2020). Heterogeneous Autoregressive Models: Survey with the Application to the Realized Volatility of Nikkei 225 Stock Index. Hiroshima University of Economics, Keizai Kenkyu.
- Zulfiqar, A. I., Ejaz, A., Spulbar, C., Birau, R., & Nethravathi, P. S. R. (2020). Measuring the Impact of Governance Quality on Stock Market Performance in Developed Countries. Economic Research-Ekonomska Istraživanja, 33(1), 3406-3426.
-
Challenges of small and medium enterprises during the COVID-19 pandemic: Case of Georgia
Amiran Maglakelidze ,
Gulnaz Erkomaishvili
doi: http://dx.doi.org/10.21511/ppm.19(4).2021.02
Problems and Perspectives in Management Volume 19, 2021 Issue #4 pp. 20-28 Views: 3080 Downloads: 1598 TO CITE АНОТАЦІЯThe COVID-19 pandemic has had a significant impact on small and medium enterprises (SMEs). The purpose of this study is to assess the impact of the COVID-19 pandemic on SMEs in Georgia, identify the challenges of SMEs in pandemic conditions, and analyze government economic policy measures. For this purpose, 102 small and medium entrepreneurs from different regions of Georgia were interviewed. The survey was conducted by sending a questionnaire through digital channels. The results were processed using data analysis, quantitative and qualitative research methods, and presented graphically. As a result, key challenges and development directions that are typical for SMEs operations in Georgia during the pandemic were identified. For 60.8% of surveyed SME owners, lockdown is the main challenge. Sales volume of 45.1% of SMEs decreased. In addition, 39.3% of the surveyed SME owners increased the innovative capabilities of a company and 37.2% increased the sales volume of a company through digital channels. The main challenge of the pandemic, lockdown, gave impetus to a change in entrepreneurial behavior. In a pandemic, entrepreneurial activity has become more favorable through digital channels. During the pandemic, there is a need to continue the government’s program of tax incentives and subsidies for SMEs. In addition, the government should promote education in the fields of entrepreneurship, innovation, and technology.
-
The Case of COVID-19 impact on the level of non-performing loans of conventional commercial banks in Indonesia
Siti Epa Hardiyanti ,
Lukmanul Hakim Aziz
doi: http://dx.doi.org/10.21511/bbs.16(1).2021.06
Banks and Bank Systems Volume 16, 2021 Issue #1 pp. 62-68 Views: 1698 Downloads: 1138 TO CITE АНОТАЦІЯThis study aims to investigate the impact of COVID-19 on the increase in bad credits at conventional commercial banks in Indonesia. The data used in this study are secondary data sourced from the Ministry of Health and from the Financial Services Authority (OJK), each of which consists of 50 data samples. The data analysis technique used in this study is simple regression analysis to determine the magnitude of the influence of COVID-19 on non-performing loans. The results of the data analysis show that COVID-19 has a significant effect on non-performing loans, and the COVID-19 variable can be used as an external indicator of the increase in non-performing loans for commercial banks in Indonesia. The implication of the research is that other researchers can make COVID-19 an external indicator of an emergency beyond human ability that can affect the level of non-performing loans. For banking, this study can be used as a reference when considering credit risk management policy during the COVID-19 pandemic.
Acknowledgment
The researchers are grateful to University of Sultan Ageng Tirtayasa for financial support. In addition, the authors sincerely apologize for the errors and mistakes found in this paper. -
Digitalization and higher education for sustainable development in the context of the Covid-19 pandemic: A content analysis approach
Ruihui Pu ,
Danai Tanamee ,
Songyu Jiang
doi: http://dx.doi.org/10.21511/ppm.20(1).2022.03
Problems and Perspectives in Management Volume 20, 2022 Issue #1 pp. 27-40 Views: 1371 Downloads: 729 TO CITE АНОТАЦІЯHigher education for sustainable development (HESD) in the Covid-19 pandemic faces different challenges. Empirically few studies to date have introduced much on the digitalization of higher education for sustainable development. This study aims to explore and explain the digitalization of HESD from different attitudes and to build linkages of the digitalization in HESD. Furthermore, the study makes content analysis where 1,200 tweets on digitalization in higher education for sustainable development are collected from Twitter, and 19 documents have further categorized information data via NVivo. In addition, 22 students and 9 instructors were invited for a semi-structured interview to further supplement this study and confirm its findings. This study finds that attitudes towards digitalization in the study area can be divided into three correlated attitude layers. Teaching attitudes and educational attitudes are the first level, and the second level is the digital platform attitude, technology use attitude, and resource attitude. Furthermore, network attitude, service attitude, and development attitude are the third level. Thus, through the analysis, this study suggests higher education institutions should make improvements in digitalized teaching, education quality via innovation, technological development, resources use, and development via creating a better digital platform or environment is essential for genuinely promoting the HESD.
