An Application of Technical Analysis in a Crisis Period: A Case Study of COVID-19 Crisis in the Thailand Stock Exchange
Article Sidebar
Main Article Content
Abstract
This research examines the effectiveness of technical analysis as an investment decision-making tool in the Stock Exchange of Thailand during times of economic crisis. Specifically, the study focuses on the use of the Relative Strength Index (RSI) and Simple Moving Average (SMA) to generate abnormal return. The findings reveal that SMA can outperform the market and increase efficiency during economic crises. However, during the COVID-19 pandemic crisis, SMA efficiency decreased, while RSI efficiency increased. The study highlights that external factors can impact the effectiveness of technical analysis and suggests that the efficiency of this investment strategy can change during crises. Therefore, investors should consider external
factors when applying technical analysis to securities. Overall, this study contributes to academic understanding of technical analysis and provides insights for investors to optimize their investment decisions during economic crises.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
บทความที่ได้รับการตีพิมพ์เป็นลิขสิทธิ์ของมหาวิทยาลัยเทคโนโลยีราชมงคลอีสาน
ข้อความที่ปรากฏในบทความแต่ละเรื่องในวารสารวิชาการเล่มนี้เป็นความคิดเห็นส่วนตัวของผู้เขียนแต่ละท่านไม่เกี่ยวข้องกับมหาวิทยาลัยเทคโนโลยีราชมงคลอีสานและคณาจารย์ท่านอื่นๆในมหาวิทยาลัยฯ แต่อย่างใด ความรับผิดชอบองค์ประกอบทั้งหมดของบทความแต่ละเรื่องเป็นของผู้เขียนแต่ละท่าน หากมีความผิดพลาดใดๆ ผู้เขียนแต่ละท่านจะรับผิดชอบบทความของตนเองแต่ผู้เดียว
References
Abuselidze, G., Slobodianyk, A., and Reznik, N. (2019). Ensuring Trading Strategies Profitability with Technical Analysis Tools and Computer Technology. SHS Web of Conferences. Vol. 71, DOI: 10.1051/shsconf/20197104005
Aguirre, A. A. A., Medina, R. A. R., and Méndez, N. D. D. (2020). Machine Learning Applied in the Stock Market Through the Moving Average Convergence Divergence (MACD) indicator. Investment Management and Financial Innovations. Vol. 17, Issue 4, pp. 44–60. DOI: 10.21511/imfi.17(4).2020.05
Ahmadi, E., Jasemi, M., Monplaisir, L., Nabavi, M. A., Mahmoodi, A., and Amini Jam, P. (2018). New Efficient Hybrid Candlestick Technical Analysis Model for Stock Market Timing on the Basis of the Support Vector Machine and Heuristic Algorithms of Imperialist Competition and Genetic. Expert Systems with Applications. Vol. 94, pp. 21-31. DOI: 10.1016/j.eswa.2017.10.023
Alexander, S. (1961). Price Movements in Speculative Markets: Trends or Random Walk? Industrial Management Review. Vol. 2, No. 2, pp. 7-26
Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., and Viratyosin, T. (2020). The Unprecedented Stock Market Reaction to COVID-19. Review of Asset Pricing Studies. Vol. 10, Issue 4, pp. 742-758. DOI: 10.1093/rapstu/raaa008
Bessembinder, H. and Chan, K. (1995). The Profitability of Technical Trading Rules in the Asian Stock Markets. Pacific-Basin Finance Journal. Vol. 3, Issue 2-3, pp. 257-284. DOI: 10.1016/0927-538X(95)00002-3
Cervelló-Royo, R., Guijarro, F., and Michniuk, K. (2015). Stock Market Trading Rule Based on Pattern Recognition and Technical Analysis: Forecasting the DJIA Index with Intraday Data. Expert Systems with Applications. Vol. 42, Issue 14, pp. 5963-5975. DOI: 10.1016/j.eswa.2015.03.017
Chan Phooi M’ng, J., and Zainudin, R. (2016). Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies. PLoS ONE. Vol. 11, Issue 8, e0160931. DOI: 10.1371/journal.pone.0160931
Chong, T. T. L. and Ng, W. K. (2008). Technical Analysis and the London Stock Exchange: Testing the MACD and RSI Rules Using the FT30. Applied Economics Letters. Vol. 15, Issue 14, pp. 1111-1114. DOI: 10.1080/13504850600993598
Dale, C. and Workman, R. (1980). The Arc Sine Law and the Treasury Bill Futures Market. Financial Analysts Journal. Vol. 36, No. 6, pp. 71-74. DOI: 10.2469/faj.v36.n6.71
Davis, S. J., Liu, D., and Sheng, X. S. (2022). Stock Prices and Economic Activity in the Time of Coronavirus. IMF Economic Review. Vol. 70, Issue 1, pp. 32-67. DOI: 10.1057/s41308-021-00146-4
de Souza, M. J. S., Ramos, D. G. F., Pena, M. G., Sobreiro, V. A., and Kimura, H. (2018). Examination of the Profi tability of Technical Analysis Based on Moving Average Strategies in BRICS. Financial Innovation. Vol. 4, Issue 1, p. 3. DOI: 10.1186/s40854-018-0087-z
Du, J. and Wong, W. -K. (2018). Predictability of Technical Analysis on Singapore Stock Market, Before and After the Asian Financial Crisis. SSRN Electronic Journal. Vol. 24, No. 1, pp. 135-150. DOI: 10.2139/ssrn.3207078
Fama, E. F. (1991). Efficient Capital II. The Journal of Finance. Vol. 46, Issue 5, pp. 1575-1617
Farias Nazário, R. T., e Silva, J. L., Sobreiro, V. A., and Kimura, H. (2017). A Literature Review of Technical Analysis on Stock Markets. The Quarterly Review of Economics and Finance. Vol. 66, pp. 115-126. DOI: 10.1016/j.qref.2017.01.014
Jen, F. C. (1970). Random Walks and Technical Theories: Some Additional Evidence: Discussion. The Journal of Finance. Vol. 25, No. 2, p. 495. DOI: 10.2307/2325498
Lo, A. W. (2004). The Adaptive Markets Hypothesis. The Journal of Portfolio Management 30th Anniversary. Vol. 30, Issue 5, pp. 15-29. DOI: 10.3905/jpm.2004.442611
Lo, A. W., Mamaysky, H., and Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. Journal of Finance. Vol. 55, Issue 4, pp. 1705-1770. DOI: 10.1111/0022-1082.00265
Lyócsa, Š., Baumöhl, E., Výrost, T., and Molnár, P. (2020). Fear of the Coronavirus and the Stock Markets. Finance Research Letters. Vol. 36, p. 101735. DOI: 10.1016/j.frl.2020.101735
Metghalchi, M., Hayes, L. A., and Niroomand, F. (2019). A Technical Approach to Equity Investing in Emerging Markets. Review of Financial Economics. Vol. 37, Issue 3, pp. 389-403. DOI: 10.1002/rfe.1041
Ng, C. C. A., Shen, J., and Rhee, S. G. (2017). Fundamental Analysis and Stock Returns in International Equity Markets. The Hong Kong Polytechnic Working Paper. Retrieved On, 20(August), pp. 1-72
Omar Farooq, M. and Hasib Reza, M. (2014). Dow Jones Islamic Market US Index: Applying Technical Analysis from a Comparative Perspective. International Journal of Islamic and Middle Eastern Finance and Management. Vol. 7, No. 3, pp. 395-420. DOI: 10.1108/IMEFM-12-2013-0134
Rosillo, R., de la Fuente, D., and Brugos, J. A. L. (2013). Technical Analysis and the Spanish Stock Exchange: Testing the RSI, MACD, Momentum and Stochastic Rules Using Spanish Market Companies. Applied Economics. Vol. 45, Issue 12, pp. 1541-1550. DOI: 10.1080/00036846.2011.631894
Tharavanij, P., Siraprapasiri, V., and Rajchamaha, K. (2015). Performance of Technical Trading Rules: Evidence from Southeast Asian Stock Markets. SpringerPlus. Vol. 4, Issue 1, pp. 1-40. DOI: 10.1186/s40064-015-1334-7
Wang, T. and Sun, Q. (2015). Why investors use technical analysis? Information discovery versus herding behavior. China Finance Review International. Vol. 5, Issue 1, pp. 53-68. DOI: 10.1108/CFRI-08-2014-0033
Yamani, E. (2021a). Can technical trading beat the foreign exchange market in times of crisis? Global Finance Journal. Vol. 48, p. 100550. DOI: 10.1016/j.gfj.2020.100550
Yamani, E. (2021b). Foreign Exchange Market Efficiency and the Global Financial Crisis: Fundamental Versus Technical Information. The Quarterly Review of Economics and Finance. Vol. 79, pp. 74-89. DOI: 10.1016/j.qref.2020.05.009
Zekai, S. and Feyyaz, Z. (2020). Coronavirus (Covid-19) and Stock Markets: the Effects of the Pandemic on the Global Economy. Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi. Vol. 7, Issue 4, pp. 1-16
Zhang, D., Hu, M., and Ji, Q. (2020). Financial Markets Under the Global Pandemic of COVID-19. Finance Research Letters. Vol. 36, p. 101528. DOI: 10.1016/j.frl.2020.101528