THE IMPACT OF INTRADAY MOMENTUM ON STOCK RETURNS: EVIDENCE FROM S&P500 AND CSI300

Simple item page
dc.contributor.authorHossain, Saddam
dc.contributor.authorGavurová, Beáta
dc.contributor.authorYuan, Xianghui
dc.contributor.authorHasan, Morshadul
dc.contributor.authorOláh, Judit
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2021-12-09T09:34:58Z
dc.date.available2021-12-09T09:34:58Z
dc.description.abstractThis paper analyzes the statistical impact of COVID-19 on the S&P500 and the CSI300 intraday momentum. This study employs an empirical method, that is, the intraday momentum method used in this research. Also, the predictability of timing conditional strategies is also used here to predict the intraday momentum of stock returns. In addition, this study aims to estimate and forecast the coefficients in the stock market pandemic crisis through a robust standard error approach. The empirical findings indicate that the intraday market behavior an unusual balanced; the volatility and trading volume imbalance and the return trends are losing overwhelmingly. The consequence is that the first half-hour return will forecast the last half-hour return of the S&P500, but during the pandemic shock, the last half-hour of both stock markets will not have a significant impact on intraday momentum. Additionally, market timing strategy analysis is a significant factor in the stock market because it shows the perfect trading time, decides investment opportunities and which stocks will perform well on this day. Besides, we also found that when the volatility and volume of the S&P500 are both at a high level, the first half-hour has been a positive impact, while at the low level, the CSI300 has a negative impact on the last half-hour. In addition, this shows that the optimistic effect and positive outlook of the stockholders for the S&P500 is in the first half-hours after weekend on Monday morning because market open during the weekend holiday, and the mentality of every stockholder’s indicate the positive impression of the stock market.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2021-4-008
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/161029
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAbreu, D., & Brunnermeier, M. K. (2002). Synchronization risk and delayed arbitrage. Journal of Financial Economics, 66(2–3), 341–360. https://doi.org/10.1016/s0304-405x(02)00227-1
dc.relation.isbasedonAdmati, A. R., & Pfleiderer, P. (1988). A Theory of Intraday Patterns: Volume and Price Variability. Review of Financial Studies, 1(1), 3–40. https://doi.org/10.1093/rfs/1.1.3
dc.relation.isbasedonAshraf, B. N. (2020). Stock markets’ reaction to COVID-19: Cases or fatalities? Research in International Business and Finance, 54, 101249. https://doi.org/https://doi.org/10.1016/j.ribaf.2020.101249
dc.relation.isbasedonAsness, C. S. C. S., Moskowitz, T. J. T. J., & Pedersen, L. H. L. H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929–985. https://doi.org/10.1111/jofi.12021
dc.relation.isbasedonBaker, M., & Wurgler, J. (2006). Investor Sentiment and the Cross-Section of Stock Returns. Journal of Finance, 61(4), 1645–1680. https://doi.org/10.1111/j.1540-6261.2006.00885.x
dc.relation.isbasedonBaker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., & Viratyosin, T. (2020). The Unprecedented Stock Market Reaction to COVID-19. Review of Asset Pricing Studies, 10(4), 742–758. https://doi.org/10.1093/rapstu/raaa008
dc.relation.isbasedonBasdekidou, V. (2017). The Momentum & Trend-Reversal as Temporal Market Anomalies. International Journal of Economics and Finance, 9(5), 1–19. https://doi.org/10.5539/ijef.v9n5p1
dc.relation.isbasedonBogousslavsky, V. (2016). Infrequent Rebalancing, Return Autocorrelation, and Seasonality. Journal of Finance, 71(6), 2967–3006. https://doi.org/10.1111/jofi.12436
dc.relation.isbasedonChu, X., Gu, Z., & Zhou, H. (2019). Intraday momentum and reversal in Chinese stock market. Finance Research Letters, 30, 83–88. https://doi.org/10.1016/j.frl.2019.04.002
dc.relation.isbasedonCohen, L., & Frazzini, A. (2008). Economic Links and Predictable Returns. Journal of Finance, 63(4), 1977–2011. https://doi.org/10.1111/j.1540-6261.2008.01379.x
dc.relation.isbasedonColeman, L., & Milanova, M. (2019). Human Computer Interaction with Multivariate Sentiment Distributions of Stocks Intraday. In C. Stephanidis (Ed.), HCI International 2019 – Posters. HCII 2019. Communications in Computer and Information Science (Vol. 1034, pp. 61–66). Cham: Springer. https://doi.org/10.1007/978-3-030-23525-3_8
dc.relation.isbasedonCushing, D., & Madhavan, A. (2000). Stock returns and trading at the close. Journal of Financial Markets, 3(1), 45–67. https://doi.org/10.1016/S1386-4181(99)00012-9
dc.relation.isbasedonDuffie, D. (2010). Presidential Address: Asset Price Dynamics with Slow-Moving Capital. Journal of Finance, 65(4), 1237–1267. https://doi.org/10.1111/j.1540-6261.2010.01569.x
dc.relation.isbasedonEasley, D., Kiefer, N. M., & O’Hara, M. (1997). The information content of the trading process. Journal of Empirical Finance, 4(2–3), 159–186. https://doi.org/10.1016/S0927-5398(97)00005-4
dc.relation.isbasedonElaut, G., Frömmel, M., & Lampaert, K. (2018). Intraday momentum in F.X. markets: Disentangling informed trading from liquidity provision. Journal of Financial Markets, 37, 35–51. https://doi.org/10.1016/j.finmar.2016.09.002
dc.relation.isbasedonEross, A., McGroarty, F., Urquhart, A., & Wolfe, S. (2019). The intraday dynamics of bitcoin. Research in International Business and Finance, 49, 71–81. https://doi.org/https://doi.org/10.1016/j.ribaf.2019.01.008
dc.relation.isbasedonGao, L., Han, Y., Zhengzi Li, S., & Zhou, G. (2018). Market intraday momentum. Journal of Financial Economics, 129(2), 394–414. https://doi.org/10.1016/j.jfineco.2018.05.009
dc.relation.isbasedonHaigh, M. S., & List, J. A. (2005). Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis. Journal of Finance, 60(1), 523–534. https://doi.org/10.1111/j.1540-6261.2005.00737.x
dc.relation.isbasedonHong, H., Torous, W., & Valkanov, R. (2007). Do industries lead stock markets? Journal of Financial Economics, 83(2), 367–396. https://doi.org/10.1016/j.jfineco.2005.09.010
dc.relation.isbasedonHou, Y., & Li, S. (2013). Price Discovery in Chinese Stock Index Futures Market: New Evidence Based on Intraday Data. Asia-Pacific Financial Markets, 20(1), 49–70. https://doi.org/10.1007/s10690-012-9158-8
dc.relation.isbasedonHutcheson, G. D. (2011). The Multivariate Social Scientist. SAGE Publications. https://doi.org/10.4135/9780857028075
dc.relation.isbasedonIto, T., & Hashimoto, Y. (2006). Intraday seasonality in activities of the foreign exchange markets: Evidence from the electronic broking system. Journal of the Japanese and International Economies, 20(4), 637–664. https://doi.org/10.1016/j.jjie.2006.06.005
dc.relation.isbasedonJain, P. C., & Joh, G.-H. (1988). The Dependence between Hourly Prices and Trading Volume. Journal of Financial and Quantitative Analysis, 23(3), 269–283. https://doi.org/10.2307/2331067
dc.relation.isbasedonJegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91. https://doi.org/10.1111/j.1540-6261.1993.tb04702.x
dc.relation.isbasedonJust, M., & Echaust, K. (2020). Stock market returns, volatility, correlation and liquidity during the COVID-19 crisis: Evidence from the Markov switching approach. Finance Research Letters, 37, 101775. https://doi.org/10.1016/j.frl.2020.101775
dc.relation.isbasedonLee, C. M. C., Mucklow, B., & Ready, M. J. (1993). Spreads, Depths, and the Impact of Earnings Information: An Intraday Analysis. The Review of Financial Studies, 6(2), 345–374. https://doi.org/10.1093/rfs/6.2.345
dc.relation.isbasedonLee, T. (2002). On algorithms for ordinary least squares regression spline fitting: A comparative study. Journal of Statistical Computation and Simulation, 72(8), 647–663. https://doi.org/10.1080/00949650213743
dc.relation.isbasedonLi, X., Yuan, X., Yuan, J., & Xu, H. (2020). Algorithms comparison on intraday index return prediction: Evidence from China. Applied Economics Letters, 28(12), 995–999. https://doi.org/10.1080/13504851.2020.1791793
dc.relation.isbasedonLi, Y., Shen, D., Wang, P., & Zhang, W. (2020). Does intraday time-series momentum exist in Chinese stock index futures market? Finance Research Letters, 35, 101292. https://doi.org/10.1016/j.frl.2019.09.007
dc.relation.isbasedonLocke, P. R., & Mann, S. C. (2005). Professional trader discipline and trade disposition. Journal of Financial Economics, 76(2), 401–444. https://doi.org/10.1016/j.jfineco.2004.01.004
dc.relation.isbasedonMahmud, A., Ding, D., & Hasan, M. M. (2021). Corporate Social Responsibility: Business Responses to Coronavirus (COVID-19) Pandemic. SAGE Open, 11(1), 2158244020988710. https://doi.org/10.1177/2158244020988710
dc.relation.isbasedonMazur, M., Dang, M., & Vega, M. (2021). COVID-19 and the march 2020 stock market crash. Evidence from S&P1500. Finance Research Letters, 38, 101690. https://doi.org/https://doi.org/10.1016/j.frl.2020.101690
dc.relation.isbasedonMoskowitz, T. J. T. J., Ooi, Y. H. Y. H., & Pedersen, L. H. L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228–250. https://doi.org/10.1016/j.jfineco.2011.11.003
dc.relation.isbasedonMurphy, D. P. D. P., & Thirumalai, R. S. R. S. (2017). Short-Term Return Predictability and Repetitive Institutional Net Order Activity. Journal of Financial Research, 40(4), 455–477. https://doi.org/10.1111/jfir.12131
dc.relation.isbasedonNarayan, P. K., Phan, D. H. B., & Narayan, S. (2018). Technology-investing countries and stock return predictability. Emerging Markets Review, 36, 159–179. https://doi.org/10.1016/j.ememar.2018.04.003
dc.relation.isbasedonNaseer, M. M., Khan, M. A., Popp, J., & Oláh, J. (2021). Firm, Industry and Macroeconomics Dynamics of Stock Returns: A Case of Pakistan Non-Financial Sector. Journal of Risk and Financial Management, 14(5), 190. https://doi.org/10.3390/jrfm14050190
dc.relation.isbasedonNewey, W. K., & West, K. D. (1987). A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix. Econometrica, 55(3), 703–708. https://doi.org/10.2307/1913610
dc.relation.isbasedonNofsinger, J. R., & Prucyk, B. (2003). Option volume and volatility response to scheduled economic news releases. Journal of Futures Markets, 23(4), 315–345. https://doi.org/https://doi.org/10.1002/fut.10064
dc.relation.isbasedonPhan, D. H. B., & Narayan, P. K. (2020). Country Responses and the Reaction of the Stock Market to COVID-19 – A Preliminary Exposition. Emerging Markets Finance and Trade, 56(10), 2138–2150. https://doi.org/10.1080/1540496X.2020.1784719
dc.relation.isbasedonRamelli, S., & Wagner, A. F. (2020). Feverish Stock Price Reactions to COVID-19. Review of Corporate Finance Studies, 9(3), 622–655. https://doi.org/10.1093/rcfs/cfaa012
dc.relation.isbasedonRapach, D., & Zhou, G. (2013). Forecasting Stock Returns. In Handbook of Economic Forecasting (Vol. 2A, pp. 328–383). Amsterdam: Elsevier. https://doi.org/10.1016/B978-0-444-53683-9.00006-2
dc.relation.isbasedonSadaf, R., Oláh, J., Popp, J., & Mate, D. (2019). Institutional ownership and simultaneity of strategic financial decisions: An empirical analysis in the case of Pakistan Stock Exchange. E&M Economics and Management, 22(1), 172–188. https://doi.org/10.15240/tul/001/2019-1-012
dc.relation.isbasedonSchulmeister, S. (2009). Profitability of technical stock trading: Has it moved from daily to intraday data? Review of Financial Economics, 18(4), 190–201. https://doi.org/https://doi.org/10.1016/j.rfe.2008.10.001
dc.relation.isbasedonSun, B., & Gao, Y. (2020). Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets. Physica A: Statistical Mechanics and Its Applications, 541, 123308. https://doi.org/https://doi.org/10.1016/j.physa.2019.123308
dc.relation.isbasedonTopcu, M., & Gulal, O. S. (2020). The impact of COVID-19 on emerging stock markets. Finance Research Letters, 36, 101691. https://doi.org/https://doi.org/10.1016/j.frl.2020.101691
dc.relation.isbasedonWagner, A. F. (2020). What the stock market tells us about the post-COVID-19 world. Nature Human Behaviour, 4(5), 440. https://doi.org/10.1038/s41562-020-0869-y
dc.relation.isbasedonWHO. (2020). Coronavirus disease (COVID-19) outbreak situation. https://www.who.int/emergencies/diseases/novelcoronavirus-%0A2019
dc.relation.isbasedonXu, Y., Bouri, E., Saeed, T., & Wen, Z. (2020). Intraday return predictability: Evidence from commodity ETFs and their related volatility indices. Resources Policy, 69(1), 101830. https://doi.org/https://doi.org/10.1016/j.resourpol.2020.101830
dc.relation.isbasedonZhang, Y., Ma, F., Shi, B., & Huang, D. (2018). Forecasting the prices of crude oil: An iterated combination approach. Energy Economics, 70, 472–483. https://doi.org/10.1016/j.eneco.2018.01.027
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectCOVID-19en
dc.subjectintraday momentumen
dc.subjectstock marketen
dc.subjectpredictabilityen
dc.subjectVolatility and Volumeen
dc.subject.classificationC13
dc.subject.classificationC33
dc.subject.classificationC41
dc.subject.classificationE44
dc.subject.classificationG14
dc.titleTHE IMPACT OF INTRADAY MOMENTUM ON STOCK RETURNS: EVIDENCE FROM S&P500 AND CSI300en
dc.typeArticleen
local.accessopen
local.citation.epage141
local.citation.spage124
local.facultyFaculty of Economics
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue4
local.relation.volume24
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
EM_4_2021_08._uprava.pdf
Size:
1.11 MB
Format:
Adobe Portable Document Format
Description:
článek
Download
Collections
Číslo 4