Intraday Return Of Winners Vs Losers Indonesian Capital Market Evidence
DOI:
https://doi.org/10.33736/ijbs.7630.2024Keywords:
volume, overnight return, intraday momentum, intraday return, USA Future Index, winner-loser portfolioAbstract
The aim of this study is to determine intraday returns in the Indonesian capital market, using sample of 177 listed Indonesian companies from 2021-2022. This study adopts a multiple linear regression analysis, where the return of the last half hour as an endogenous variable consists of winners and losers, the return of the first half hour of trading, the volume of the first half hour, overnight returns, and the USA index futures as an exogenous variable. The originality of this research aims to demonstrate empirical evidence on intraday returns by distinguishing winner & loser stocks and the relationship between the intraday returns of winners and losers with volume, overnight, and US index futures in the emerging market (Indonesia). We find that the first half hour of trading can impact future return. The return of the first thirty minutes is significantly positive on the return of the last thirty minutes for both winner and loser stocks. Further, the volume of the first half hour and the overnight return both positively influences on the last half hour return of the day for loser stocks. This study can offer valuable insights for investment portfolio strategies, especially regarding intraday returns. The findings of this research prove to be a valuable resource for investors when devising investment strategies in the stock market. Additionally, it provides guidance for regulators in establishing rules for stock trading, particularly in transactions involving trading robots.
References
Adrianto, F., & Hamidi, M. (2020). Analysis of Retail Investment Behaviour in Indonesian Stock Market. Academy of Accounting and Financial Studies Journal, 24(2), 2635-2649.
Aitken, M., Cumming, D., & Zhan, F. (2015). High frequency trading and end-of-day price dislocation. Journal of Banking and Finance, 59(June), 330-349. https://doi.org/10.1016/j.jbankfin.2015.06.011
https://doi.org/10.1016/j.jbankfin.2015.06.011
Andersen, T. G., Riva, R., Thyrsgaard, M., & Todorov, V. (2022). Intraday cross-sectional distributions of systematic risk. Journal of Econometrics, 235(2), 1394-1418. https://doi.org/10.1016/j.jeconom.2022.11.001
https://doi.org/10.1016/j.jeconom.2022.11.001
Aslam, F., Memon, B. A., & Mughal, K. S. (2020). Risk-adjusted and Bonferroni-adjusted seasonality in emerging Asian stock markets. Economic Journal of Emerging Markets, 12(1), 80-92. https://doi.org/10.20885/ejem.vol12.iss1.art7
https://doi.org/10.20885/ejem.vol12.iss1.art7
Azevedo, V. (2022). Analysts' Underreaction and Momentum Strategies. Journal of Economic Dynamics and Control, 49(2), 1-49. https://doi.org/10.2139/ssrn.4095711
https://doi.org/10.2139/ssrn.4095711
Blau, B. M., Griffith, T. G., & Whitby, R. J. (2018). The maximum bid-ask spread. Journal of Financial Markets, 41, 1-16. https://doi.org/10.1016/j.finmar.2018.09.003
https://doi.org/10.1016/j.finmar.2018.09.003
Boehmer, E., Fong, K., & Wu, J. (2021). Algorithmic Trading and Market Quality: International evidence. Journal of Financial and Quantitative Analysis, 56(8), 2659-2688.
https://doi.org/10.1017/S0022109020000782
Bogousslavsky, V. (2016). Infrequent Rebalancing, Return Autocorrelation, and Seasonality. Journal of Finance, 71(6), 2967-3006. https://doi.org/10.1111/jofi.12436
https://doi.org/10.1111/jofi.12436
Bogousslavsky, V. (2021). The cross-section of intraday and overnight returns. Journal of Financial Economics, 141(1), 172-194. https://doi.org/10.1016/j.jfineco.2020.07.020
https://doi.org/10.1016/j.jfineco.2020.07.020
Branch, B. S., & Ma, A. (2012). Overnight Return, the Invisible Hand Behind the Intraday Return? A Retrospective. Journal of Applied Finance, 22(2), 1-11. https://doi.org/10.2139/ssrn.3259614
https://doi.org/10.2139/ssrn.3259614
Brogaard, J., Hendershott, T., & Riordan, R. (2014). High-frequency trading and price discovery. Review of Financial Studies, 27(8), 2267-2306. https://doi.org/10.1093/rfs/hhu032
https://doi.org/10.1093/rfs/hhu032
Chae, J., & Kim, R. (2020). Contrarian profits of the firm-specific component on stock returns. Pacific Basin Finance Journal, 61, 101176. https://doi.org/10.1016/j.pacfin.2019.101176 Chordia, T., Roll, R., & Subrahmanyam, A. (2011). Recent trends in trading activity and market quality. Journal of Financial Economics, 101(2), 243-263. https://doi.org/10.1016/j.jfineco.2011.03.008
https://doi.org/10.1016/j.jfineco.2011.03.008
Chu, X., & Song, S. (2023). Cross-sectional reversal of intraday returns and investor heterogeneity in an emerging market. Borsa Istanbul Review, 23(3), 614-627. https://doi.org/10.1016/j.bir.2023.01.002
https://doi.org/10.1016/j.bir.2023.01.002
Dávila, E., & Parlatore, C. (2021). Trading Costs and Informational Efficiency. Journal of Finance, 76(3), 1471-1539. https://doi.org/10.1111/jofi.13008
https://doi.org/10.1111/jofi.13008
Devianto, D., Maiyastri, Randy, Hamidi, M., Maryati, S., & Wirahadi Ahmad, A. (2018). Efficiency analysis of optimal portfolio selection for stocks in LQ45 index. Proceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation: Toward A New Paradigm for the Design of Assistive Technology in Smart Home Care, 78-83. https://doi.org/10.1109/ICAITI.2018.8686713
https://doi.org/10.1109/ICAITI.2018.8686713
Dong, L., Dai, Y., Haque, T., Kot, H. W., & Yamada, T. (2022). Coskewness and reversal of momentum returns: The US and international evidence. Journal of Empirical Finance, 69(2), 241-264. https://doi.org/10.1016/j.jempfin.2022.10.004
https://doi.org/10.1016/j.jempfin.2022.10.004
Du, Q., Liang, D., Chen, Z., & Tu, J. (2022). Concept links and return momentum. Journal of Banking and Finance, 134, 106329. https://doi.org/10.1016/j.jbankfin.2021.106329
https://doi.org/10.1016/j.jbankfin.2021.106329
Gao, B., & Liu, X. (2020). Intraday sentiment and market returns. International Review of Economics and Finance, 69(3), 48-62. https://doi.org/10.1016/j.iref.2020.03.010
https://doi.org/10.1016/j.iref.2020.03.010
Gao, 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
https://doi.org/10.1016/j.jfineco.2018.05.009
Hamidi, M., & Adrianto, F. (2022). Government officers: Do they have a better retirement planning? Kasetsart Journal of Social Sciences, 43, 645-652.
https://doi.org/10.34044/j.kjss.2022.43.3.15
Han, Y., Huang, D., Huang, D., & Zhou, G. (2022). Expected return, volume, and mispricing. Journal of Financial Economics, 143(3), 1295-1315. https://doi.org/10.1016/j.jfineco.2021.05.014
https://doi.org/10.1016/j.jfineco.2021.05.014
Hendershott, T., Livdan, D., & Rösch, D. (2020). Asset pricing: A tale of night and day. Journal of Financial Economics, 138(3), 635-662. https://doi.org/10.1016/j.jfineco.2020.06.006
https://doi.org/10.1016/j.jfineco.2020.06.006
Heston, S. L., Korajczyk, R. A., & Sadka, R. (2010). Intraday patterns in the cross-section of stock returns. Journal of Finance, 65(4), 1369-1407. https://doi.org/10.1111/j.1540-6261.2010.01573.x
https://doi.org/10.1111/j.1540-6261.2010.01573.x
Hsieh, S. F., Chan, C. Y., & Wang, M. C. (2020). Retail investor attention and herding behavior. Journal of Empirical Finance, 59, 109-132. https://doi.org/10.1016/j.jempfin.2020.09.005
https://doi.org/10.1016/j.jempfin.2020.09.005
Huang, D., Li, J., Wang, L., & Zhou, G. (2020). Time series momentum: Is it there? Journal of Financial Economics, 135(3), 774-794. https://doi.org/10.1016/j.jfineco.2019.08.004
https://doi.org/10.1016/j.jfineco.2019.08.004
Hussain, S. M. (2011). The Intraday Behaviour of Bid-Ask Spreads, Trading Volume and Return Volatility: Evidence from DAX30. International Journal of Economics and Finance, 3(1), 23-34. https://doi.org/10.5539/ijef.v3n1p23
https://doi.org/10.5539/ijef.v3n1p23
İpek, İ. (2021). The relevance of international marketing strategy to emerging-market exporting firms: from a systematic review towards a conceptual framework. International Marketing Review, 38(2), 205-248. https://doi.org/10.1108/IMR-02-2020-0017
https://doi.org/10.1108/IMR-02-2020-0017
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91. http://onlinelibrary.wiley.com/doi/10.1111/j.1540-6261.1993.tb04702.x/abstract
https://doi.org/10.1111/j.1540-6261.1993.tb04702.x
Kang, J., Lin, S., & Xiong, X. (2022). What drives intraday reversal? Illiquidity or liquidity oversupply?. Journal of Economic Dynamics and Control, 136, 1-73. https://doi.org/10.1016/j.jedc.2022.104313
https://doi.org/10.1016/j.jedc.2022.104313
Karaca, Y., Zhang, Y. D., & Muhammad, K. (2020). Characterizing complexity and self-similarity based on Fractal and Entropy analyses for Stock Market Forecast Modelling. Expert Systems with Applications, 144, 113098. https://doi.org/10.1016/j.eswa.2019.113098
https://doi.org/10.1016/j.eswa.2019.113098
Kia, A. N., Haratizadeh, S., & Shouraki, S. B. (2018). A hybrid supervised semi-supervised graph-based model to predict one-day ahead movement of global stock markets and commodity prices. Expert Systems with Applications, 105, 159-173. https://doi.org/10.1016/j.eswa.2018.03.037
https://doi.org/10.1016/j.eswa.2018.03.037
Kim, B., & Suh, S. (2021). Overnight stock returns, intraday returns, and firm-specific investor sentiment. North American Journal of Economics and Finance, 55(3), 101287. https://doi.org/10.1016/j.najef.2020.101287
https://doi.org/10.1016/j.najef.2020.101287
Li, Z., Sakkas, A., & Urquhart, A. (2022). Intraday time series momentum: Global evidence and links to market characteristics. Journal of Financial Markets, 57, 100619. https://doi.org/10.1016/j.finmar.2021.100619
https://doi.org/10.1016/j.finmar.2021.100619
Liu, Q., Guo, H., & Wei, X. (2015). Negative overnight returns: China's security markets. Information Technology and Quantitative Management (ITQM), 55(1), 980-989. https://doi.org/10.1016/j.procs.2015.07.105
https://doi.org/10.1016/j.procs.2015.07.105
Lou, D., Polk, C., & Skouras, S. (2019). A tug of war: Overnight versus intraday expected returns. Journal of Financial Economics, 134(1), 192-213. https://doi.org/10.1016/j.jfineco.2019.03.011
https://doi.org/10.1016/j.jfineco.2019.03.011
Maheshwari, S., & Dhankar, R. S. (2017). Momentum Anomaly: Evidence from the Indian Stock Market. Journal of Advances in Management Research, 14(1), 3-22. https://doi.org/10.1108/JAMR-11-2015-0081
https://doi.org/10.1108/JAMR-11-2015-0081
Malagrino, L. S., Roman, N. T., & Monteiro, A. M. (2018). Forecasting stock market index daily direction: A Bayesian Network approach. Expert Systems with Applications, 105, 11-22. https://doi.org/10.1016/j.eswa.2018.03.039
https://doi.org/10.1016/j.eswa.2018.03.039
Malceniece, L., Malcenieks, K., & Putniņš, T. J. (2019). High frequency trading and comovement in financial markets. Journal of Financial Economics, 134(2), 381-399. https://doi.org/10.1016/j.jfineco.2018.02.015
https://doi.org/10.1016/j.jfineco.2018.02.015
Menkveld, A. J. (2014). High-frequency traders and market structure. Financial Review, 49(2), 333-344. https://doi.org/10.1111/fire.12038
https://doi.org/10.1111/fire.12038
Narayan, P. K., & Sharma, S. S. (2016). Intraday return predictability, portfolio maximisation, and hedging. Emerging Markets Review, 28, 105-116. https://doi.org/10.1016/j.ememar.2016.08.017
https://doi.org/10.1016/j.ememar.2016.08.017
Qiao, K., & Dam, L. (2020). The overnight return puzzle and the "T+1" trading rule in Chinese stock markets. Journal of Financial Markets, 50, 100534. https://doi.org/10.1016/j.finmar.2020.100534
https://doi.org/10.1016/j.finmar.2020.100534
Renault, T. (2017). Intraday online investor sentiment and return patterns in the U.S. stock market. Journal of Banking and Finance, 84, 25-40. https://doi.org/10.1016/j.jbankfin.2017.07.002
https://doi.org/10.1016/j.jbankfin.2017.07.002
Robbani, M. G., & Bhuyan, R. (2016). Introduction of Futures and Options on a Stock Index and their Impact on the Trading Volume and Volatility: Empirical Evidence from the DJIA Components. In S. Satchell (Eds.), Derivatives and Hedge Funds (pp. 187-201). Palgrave Macmillan. https://doi.org/10.1057/9781137554178_9
https://doi.org/10.1057/9781137554178_9
Sadalia I., Irawati N., Hamidi M., Giriati G., Yuliana S. (2019). How the financial opennes accelerates the economic growth of leading Asean economies. Journal of Security and Sustainability Issues, 9(2), 473-487.
https://doi.org/10.9770/jssi.2019.9.2(9)
Seok, S. I., Cho, H., & Ryu, D. (2021). Stock Market's responses to intraday investor sentiment.North American Journal of Economics and Finance, 58, 101516. https://doi.org/10.1016/j.najef.2021.101516
https://doi.org/10.1016/j.najef.2021.101516
Sun, L., Najand, M., & Shen, J. (2016). Stock return predictability and investor sentiment: A high-frequency perspective. Journal of Banking and Finance, 73, 147-164. https://doi.org/10.1016/j.jbankfin.2016.09.010
https://doi.org/10.1016/j.jbankfin.2016.09.010
Wen, Z., Bouri, E., Xu, Y., & Zhao, Y. (2022). Intraday return predictability in the cryptocurrency markets: Momentum, reversal, or both. North American Journal of Economics and Finance, 62, 101733. https://doi.org/10.1016/j.najef.2022.101733
https://doi.org/10.1016/j.najef.2022.101733
Wood, R. A., McInish, T. H., & ORD, J. K. (1985). An investigation of transactions data for NYSE Stocks. The Journal of Finance, 40(3), 723-739. https://doi.org/10.1111/j.1540-6261.1985.tb04996.x
https://doi.org/10.1111/j.1540-6261.1985.tb04996.x
Wouassom, A., Muradoğlu, Y. G., & Tsitsianis, N. (2022). Global momentum: The optimal trading approach. Journal of Behavioral and Experimental Finance, 36, 100756. https://doi.org/10.1016/j.jbef.2022.100756
https://doi.org/10.1016/j.jbef.2022.100756
Xiong, X., Meng, Y., Li, X., & Shen, D. (2020). Can overnight return really serve as a proxy for firm-specific investor sentiment? Cross-country evidence. Journal of International Financial Markets, Institutions & Money, 64(92), 101173. https://doi.org/10.1016/j.intfin.2019.101173
https://doi.org/10.1016/j.intfin.2019.101173
Zhang, Y., Ma, F., & Zhu, B. (2019). Intraday momentum and stock return predictability: Evidence from China. Economic Modelling, 76, 319-329. https://doi.org/10.1016/j.econmod.2018.08.009
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 UNIMAS Publisher
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright Transfer Statement for Journal
1) In signing this statement, the author(s) grant UNIMAS Publisher an exclusive license to publish their original research papers. The author(s) also grant UNIMAS Publisher permission to reproduce, recreate, translate, extract or summarize, and to distribute and display in any forms, formats, and media. The author(s) can reuse their papers in their future printed work without first requiring permission from UNIMAS Publisher, provided that the author(s) acknowledge and reference publication in the Journal.
2) For open access articles, the author(s) agree that their articles published under UNIMAS Publisher are distributed under the terms of the CC-BY-NC-SA (Creative Commons Attribution-Non Commercial-Share Alike 4.0 International License) which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original work of the author(s) is properly cited.
3) For subscription articles, the author(s) agree that UNIMAS Publisher holds copyright, or an exclusive license to publish. Readers or users may view, download, print, and copy the content, for academic purposes, subject to the following conditions of use: (a) any reuse of materials is subject to permission from UNIMAS Publisher; (b) archived materials may only be used for academic research; (c) archived materials may not be used for commercial purposes, which include but not limited to monetary compensation by means of sale, resale, license, transfer of copyright, loan, etc.; and (d) archived materials may not be re-published in any part, either in print or online.
4) The author(s) is/are responsible to ensure his or her or their submitted work is original and does not infringe any existing copyright, trademark, patent, statutory right, or propriety right of others. Corresponding author(s) has (have) obtained permission from all co-authors prior to submission to the journal. Upon submission of the manuscript, the author(s) agree that no similar work has been or will be submitted or published elsewhere in any language. If submitted manuscript includes materials from others, the authors have obtained the permission from the copyright owners.
5) In signing this statement, the author(s) declare(s) that the researches in which they have conducted are in compliance with the current laws of the respective country and UNIMAS Journal Publication Ethics Policy. Any experimentation or research involving human or the use of animal samples must obtain approval from Human or Animal Ethics Committee in their respective institutions. The author(s) agree and understand that UNIMAS Publisher is not responsible for any compensational claims or failure caused by the author(s) in fulfilling the above-mentioned requirements. The author(s) must accept the responsibility for releasing their materials upon request by Chief Editor or UNIMAS Publisher.
6) The author(s) should have participated sufficiently in the work and ensured the appropriateness of the content of the article. The author(s) should also agree that he or she has no commercial attachments (e.g. patent or license arrangement, equity interest, consultancies, etc.) that might pose any conflict of interest with the submitted manuscript. The author(s) also agree to make any relevant materials and data available upon request by the editor or UNIMAS Publisher.
