Half-life estimates of COVID19, Investor Sentiment, and the Stock Market
Keywords:
COVID19, Half-life Estimates, Investor Sentiment, Stock MarketAbstract
The half-life is used to estimate the adjustment speed of a variable to a new equilibrium point after being affected by the impulse response of a unit of shocks. The paper examines the adjustment speed of COVID19, investor sentiment, and the stock market through half-life estimates over the period from January 2020 to August 2022. To achieve the research goal, the study is based on the autoregressive model and the augmented Dickey-Fuller test results to estimate the half-lives of the variables. The results prove a valid short-term association and fast adjustment speed of COVID19, investor sentiment, and the stock market. The results of the estimates probably contribute to investor decision-making, risk avoidance, and policy proposals.
References
Al-Qudah, A. A., & Houcine, A. (2021). Stock markets' reaction to COVID-19: Evidence from the six WHO regions. Journal of Economic Studies, 49(2), 274-289.
Albulescu, C. T. (2020). COVID-19 and the United States financial markets' volatility. Finance Research Letters, 38, 101699.
Ali, M., Alam, N., & Rizvi, S. A. R. (2020). Coronavirus (COVID-19)—An epidemic or pandemic for financial markets. Journal of Behavioral and Experimental Finance, 27, 100341.
Ausloos, M., Zhang, Y., & Dhesi, G. (2020). Stock index futures trading impact on spot price volatility. The CSI 300 studied with a TGARCH model. Expert Systems with Applications, 160, 113688.
Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Economic Management Journal, 61(4), 1645-1680.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129-152.
Bouteska, A., Mefteh-Wali, S., & Dang, T. (2022). Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic. Technological Forecasting and Social Change, 184, 121999.
Campbell, J. Y., & Mankiw, N. G. (1987). Are output fluctuations transitory?. The Quarterly Journal of Economics, 102(4), 857-880.
Chau, F., Deesomsak, R., & Koutmos, D. (2016). Does investor sentiment really matter?. International Review of Financial Analysis, 48, 221-232.
Cheung, Y. W., & Lai, K. S. (2000). On the purchasing power parity puzzle. Journal of International Economics, 52(2), 321-330.
China investor sentiment index. (2020-2022). Retrieved from https://www.nsd.pku.edu.cn/zsfb/zgtzzqxzs/index.htm
Choi, C.-Y., Mark, N. C., & Sul, D. (2004). Unbiased estimation of the Half-life to PPP convergence in panel data. Journal of Money, Credit and Banking, 38, 921-938.
Christidou, M., & Panagiotidis, T. (2010). Purchasing power parity and the European single currency: Some new evidence. Economic Modelling, 27(5), 1116-1123.
Debata, B., Dash, S. R., & Mahakud, J. (2018). Investor sentiment and emerging stock market liquidity. Finance Research Letters, 26, 15-31.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431.
Dickey, D. A., Hasza, D. P., & Fuller, W. A. (1984). Testing for unit roots in seasonal time series. Journal of the American Statistical Association, 79(386), 355-367.
Edmans, A., Garc´ıa, D., & Norli, Ø. (2007). Sports sentiment and stock returns. The Journal of Finance, 62(4), 1967-1998.
Gil-Alana, L. A., & Claudio-Quiroga, G. (2020). The COVID-19 impact on the Asian stock markets. Asian Economics Letters, 1(2), 17656.
The global COVID19 cumulative deaths. (2022).
Retrieved from https://covid19.who.int/data
Goel, G., & Dash, S. R. (2021). Investor sentiment and government policy interventions: Evidence from COVID-19 spread. Journal of Financial Economic Policy, 14(2), 242-267.
Guo, K., Sun, Y., & Qian, X. (2017). Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market. Physica A: Statistical Mechanics and its Applications, 469, 390-396.
Harjoto, M. A., Rossi, F., & Paglia, J. K. (2021). COVID-19: Stock market reactions to the shock and the stimulus. Applied Economics Letters, 28(10), 795-801.
Haroon, O., & Rizvi, S. A. R. (2020). Flatten the curve and stock market liquidity – an inquiry into emerging economies. Emerging Markets Finance and Trade, 56(10), 2151-2161.
He, P., Sun, Y., Zhang, Y., & Li, T. (2020). COVID–19’s impact on stock prices across different sectors—An event study based on the Chinese stock market. Emerging Markets Finance and Trade, 56(10), 2198-2212
Huang, W., & Zheng, Y. (2020). COVID-19: Structural changes in the relationship between investor sentiment and crude oil futures price. Energy Research Letters, 1(2), 13685.
Kumari, J. (2019). Investor sentiment and stock market liquidity: Evidence from an emerging economy. Journal of Behavioral and Experimental Finance, 23, 166-180.
The latest situation of COVID19 pandemic in China. (2020-2022). Retrieved from http://www.nhc.gov.cn/
Liu, K. (2021). The effects of COVID-19 on Chinese stock markets: An EGARCH approach. Economic and Political Studies, 9(2), 148-165.
Lucey, B. M., & Dowling, M. (2005). The role of feelings in investor decision-making. Journal of Economic Surveys, 19(2), 211-237.
Mazumder, S., & Saha, P. (2021). COVID-19: Fear of pandemic and short-term IPO performance. Finance Research Letters, 43, 101977.
Mazur, M., Dang, M., & Vega, M. (2021). COVID-19 and the march 2020 stock market crash. Evidence from S&P1500. Finance Research Letters, 38, 101690.
Morshed, A. K. M. M., K.Ahn, S., & Lee, M. ( 2006). Price convergence among Indian cities: A cointegration approach. Journal of Asian Economics, 17(6), 1030-1043.
Narayan, P. K., Phan, D. H. B., & Liu, G. (2021). COVID-19 lockdowns, stimulus packages, travel bans, and stock returns. Finance Research Letters, 38, 101732.
Nelson, C. R., & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series: Some evidence and implications. Journal of Monetary Economics, 10(2), 139-162.
Qiao, G., Teng, Y., Lia, W., & Liu, W. (2019). Improving volatility forecasting based on Chinese volatility index information: Evidence from CSI 300 index and futures markets. The North American Journal of Economics and Finance, 49, 133-151.
Renault, T. (2017). Intraday online investor sentiment and return patterns in the U.S. stock market. Journal of Banking & Finance, 84, 25-40.
Rupande, L., Muguto, H. T., & Muzindutsi, P.-F. (2019). Investor sentiment and stock return volatility: Evidence from the Johannesburg Stock Exchange. Cogent Economics & Finance, 7(1), 1600233.
Schmeling, M. (2009). Investor sentiment and stock returns: Some international evidence. Journal of Empirical Finance, 16(3), 394-408.
Shu, H.-C. (2010). Investor mood and financial markets. Journal of Economic Behavior & Organization, 76(2), 267-282.
Six PHEICs in the world since the 21st century. (2022). Retrieved from https://www.euro.who.int/en/health-topics/health-emergencies/international-health-regulations/event-reporting-and-review/reporting-events/ihr-committees/ihr-emergency-committee
Sun, Y., Bao, Q., & Lu, Z. (2021). Coronavirus (Covid-19) outbreak, investor sentiment, and medical portfolio: Evidence from China, Hong Kong, Korea, Japan, and U.S. Pacific-Basin Finance Journal, 65, 101463.
Timeline: WHO's COVID19 response. (2022). Retrieved from
https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline#!
Van Hoang, T. H., & Syed, Q. R. (2021). Investor sentiment and volatility prediction of currencies and commodities during the COVID-19 pandemic. Asian Economics Letters, 1(4), 18642.
Wan, D., Xue, R., Linnenluecke, M., Tian, J., & Shan, Y. (2021). The impact of investor attention during COVID-19 on investment in clean energy versus fossil fuel firms. Finance Research Letters, 43, 101955.
Xu, Initial. & Pu, W. (2022). ETFs, arbitrage activity, and stock market efficiency: Evidence from Chinese CSI 300 ETFs. Economic Analysis and Policy, 73, 1-9.
Yang, C., & Zhou, L. (2015). Investor trading behavior, investor sentiment and asset prices. North American Journal of Economics & Finance, 34, 42-62.
Zhang, D., Hua, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 10528.
Zhou, W., Rao, W., & Lu, S. (2020). Market stability analysis after the circuit breaker for the CSI 300 energy index. Finance Research Letters, 34, 101348.
Akram, F. (2003). Real equilibrium exchange rates for Norway. Explaining movements in the Norwegian exchange rate, 32, 53-86.
Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and Stock Market Volatility: An Industry Level Analysis. Finance Research Letters, 37, 101748.
Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307-343.
Beer, F., Watfa, M., & Zouaoui, M. (2012). Is Sentiment Risk Priced By Stock Market? Journal of Applied Business Research, 28(4), 683-700.
Campbell, J. Y., & Mankiw, N. G. (1987). Are Output Fluctuations Transitory? The Quarterly Journal of Economics, 102(4), 857-880.
Cevik, E., Altinkeski, B. K., Cevik, E. I., & Dibooglu, S. (2022). Investor sentiments and stock markets during the COVID-19 pandemic. Financial Innovation, 8(1), 69.
Chen, N., Roll, R., & Ross, S. A. (1986). Economic Forces and the Stock Market. The Journal of Business, 59(3), 383-403
Cheung, Y. W., & Lai, K. S. (2000). On the purchasing power parity puzzle. Journal of International Economics, 52(2), 321-330.
Choi, C.-Y., Mark, N. C., & Sul, D. (2004). Unbiased Estimation of the Half-Life to PPP Convergence in Panel Data. Journal of Money, Credit and Banking, 38, 921-938.
Christidou, M., & Panagiotidis, T. (2010). Purchasing Power Parity and the European single currency: Some new evidence. Economic Modelling, 27(5), 1116-1123.
Corbet, S., Hou, Y., Hu, Y., & Oxley, L. (2022). Did COVID-19 tourism sector supports alleviate investor fear? Annals of Tourism Research, 95, 103434.
CSI300 index. (2020-2022). Retrieved from http://www.wind.com.cn
Dhankar, R. S. (2019). Investor Sentiment and Investment Decision-Making. In Risk-Return Relationship and Portfolio Management (pp. 307-319): Springer.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431.
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
Dickey, D. A., Hasza, D. P., & Fuller, W. A. (1984). Testing for unit roots in seasonal time series. Journal of the American Statistical Association, 79(386), 355-367.
Fiske, S. T., Gilbert, D. T., & Lindzey, G. (2010). Handbook of Social Psychology (Vol. 2): John Wiley & Sons.
Gao, X., Ren, Y., & Umar, M. (2021). To what extent does COVID-19 drive stock market volatility? A comparison between the U.S. and China. Economic Research-Ekonomska Istraživanja, 35(1), 1686-1706.
Granville, J. E. (1960). A strategy of daily stock market timing for maximum profit: Prentice-Hall.
Harjoto, M. A., Rossi, F., Lee, R., & Sergi, B. S. (2021). How do equity markets react to COVID-19? Evidence from emerging and developed countries. Journal of Economics and Business, 115, 105966.
Haroon, O., & Rizvi, S. A. R. (2020). COVID-19: Media coverage and financial markets behavior—A sectoral inquiry. Journal of Behavioral and Experimental Finance, 27, 100343.
Liu, K. (2021). The effects of COVID-19 on Chinese stock markets: an EGARCH approach. Economic and Political Studies, 9.
Liu, Z., Huynh, T. L. D., & Dai, P.-F. (2021). The impact of COVID-19 on the stock market crash risk in China. Research in International Business and Finance, 57, 101419.
Mezghani, T., Boujelbène, M., & Elbayar, M. (2021). Impact of COVID‐19 pandemic on risk transmission between googling investor’s sentiment, the Chinese stock and bond markets. China Finance Review International, 11(3), 322-348.
Morshed, A. K. M. M., K.Ahn, S., & Lee, M. ( 2006). Price convergence among Indian cities: A cointegration approach. Journal of Asian Economics, 17(6), 1030-1043.
Nelson, C. R., & Plosser, C. R. (1982). Trends and random walks in macroeconmic time series: some evidence and implications. Journal of Monetary Economics, 10(2), 139-162.
Nofsinger, J. R. (2005). Social mood and financial economics. Journal of Behavioral Finance, 6(3), 144-160.
Onali, E. (2020). Covid-19 and stock market volatility.
Report of the global COVID19 cumulative comfirmed cases (2022). Retrieved from https://covid19.who.int/data
Report of the global COVID19 cumulative deaths. (2022). Retrieved from https://covid19.who.int/data
Ronaghi, F., Salimibeni, M., Naderkhani, F., & Mohammadi, A. (2022). COVID19-HPSMP: COVID-19 adopted Hybrid and Parallel deep information fusion framework for stock price movement prediction. Expert Systems with Applications, 187, 115879.
Shefrin, H. (2002). Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing: Oxford University Press.
Six PHEICs in the world since the 21st century. (2022). Retrieved from https://www.euro.who.int/en/health-topics/health-emergencies/international-health-regulations/event-reporting-and-review/reporting-events/ihr-committees/ihr-emergency-committee
Tetlock, P. C. (2014). Information transmission in finance. Annual Review of Financial Economics, 6(1), 365-384.
Timeline: WHO's COVID19 response. (2022). Retrieved from https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline#!
Westerhoff, F. (2012). Interactions between the Real Economy and the Stock Market: A Simple Agent-Based Approach. Discrete dynamics in nature and society, 2012, 504840. Retrieved from https://doi.org/10.1155/2012/504840
Zorzi, M. C., Rubaszek, M., & Mućk, J. (2013). Real exchange rate forecasting: a calibrated half-life PPP model can beat the random walk. European Central Bank, 1576.
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