New IJF now accepts submissions exclusively via the Editorial Scholar portal — a dedicated submission & review system.
Go to Editorial Scholar →
Associated Management Consultants Pvt. Ltd. | COPE Member
Scopus Q2 UGC-CARE |
Indian Journal of Finance logo

Indian Journal of Finance

ISSN: 0973-8711 Frequency: Monthly Peer Review: Double-blind Published since: 2007 Language: English
A publication of AMCPL
amcon.co.in
New Delhi, India
Indexed in: Scopus Q2 UGC-CARE Group II Google Scholar J-Gate NISCAIR Crossref

Original Article

Open Access Original Article

Efficiency of RSI Investment Strategy : A Comparative Study of Saudi Arabia, India, and China

Nidhi1,  Narinder Singh Malik2,  Rajat Singla3

1 Research Scholar , Haryana School of Business, Guru Jambheshwar University of Science and Technology, Hisar - 125 011, Haryana

2 Professor, Haryana School of Business, Guru Jambheshwar University of Science and Technology, Hisar - 125 011, Haryana

3 Assistant Professor, Sri Atmanand Jain College, Ambala - 134 003, Haryana

Volume 17
Issue 11
Pages 50–61
Year 2023
Received: Sept. 10, 2022 Accepted: Aug. 20, 2023 Published: Nov. 1, 2023
Abstract

Purpose: The present study is focused on testing the performance of the relative strength index (RSI) minutely on daily prices of stock indices of three sample countries. As the interest in investing in the stock market is growing day by day, the need to test the performance of technical indicators is also enhanced.

Methodology: The closing prices of three indices from the sample markets were investigated for 14 years, from January 2008 to December 2021, by applying the 30/70 rule of the RSI. The whole period of sample data from 2008 to 2021 has been divided into two smaller sub-periods of 7 years each in order to test the performance of the oscillator during the short period. Sub-period I is from January 2008 to December 2014; Sub-period II is from January 2015 to December 2021. While comparing the buy and hold strategy with RSI, one form has assumed that once the buy or sell decision is made, the same will be held for 10 days.

Findings: A 1% significance level was used to find the majority of the results to be statistically significant. Twenty-seven places, or 50% at the 1% level, and three results, or 5.55% at the 5% and 10% levels, were determined to be statistically significant out of the 54 total results. At various levels, 61.12% of the long, short, and long-short positions are determined to be statistically significant.Practical

Implications: RSI is the most frequently used oscillator by investors for making investment decisions; thus, it becomes essential to minutely study the profitability of the oscillator academically. Our study is not free from limitations and allows scope for future researchers to study the performance of oscillators along with other techniques of technical trading rule, and it can be tested on different samples of markets.

Originality: The previous research focused either on testing moving averages or testing plain crossover rules of RSI. The current work tested different forms of the oscillator, applying a holding period of days.

Keywords Relative Strength Index (RSI) Stock Markets Indices Technical Trading Rule 30/70 (TTR) Transaction Cost (TC)
How to Cite

Nidhi, Narinder Singh Malik, Rajat Singla (2023). Efficiency of RSI Investment Strategy : A Comparative Study of Saudi Arabia, India, and China. Indian Journal of Finance, 17(11), 50–61. https://doi.org/10.17010/ijf/2023/v17i11/171931

References
  1. Agrawal, M., Khan, A. U., & Shukla, P. K. (2019). Stock price prediction using technical indicators: A predictive model using optimal deep learning. International Journal of Recent Technology and Engineering (IJRTE), 8(2), 2297–2305. https://doi.org/10.35940/ijrteb3048.078219
  2. Agustin, I. N. (2019). The integration of fundamental and technical analysis in predicting the stock price. Jurnal Manajemen Maranatha, 18(2), 93–102. https://doi.org/10.28932/jmm.v18i2.1611
  3. Allen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51(2), 245–271. https://doi.org/10.1016/S0304-405X(98)00052-X
  4. Alsabban, S., & Alarfaj, O. (2019). An empirical analysis of behavioral finance in the Saudi stock market: Evidence of overconfidence behavior. International Journal of Economics and Financial Issues, 10(1), 73–86. https://doi.org/10.32479/ijefi.8920
  5. Boobalan, C. (2014). Technical analysis in select stocks of Indian companies. International Journal of Business and Administration Research Review, 2(4), 26–36.
  6. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731–1764. https://doi.org/10.1111/j.1540-6261.1992.tb04681.x
  7. Chitra, R. (2011). Technical analysis on selected stocks of energy sector. International Journal of Management & Business Studies, 1(1), 42–46.
  8. Choudhary, P., & Bhatnagar, A. (2018). A study on technical analysis of selected PSUs and their market movements with relation to BSE. ELK Asia Pacific Journal of Finance and Risk Management, 9(2), 1–18.
  9. Hilliard, J., Schwartz, A., & Squire, J. (2013). A test of technical analysis: Matching time displaced generalized patterns. Financial Management, 42(2), 291–314. https://doi.org/10.1111/fima.12002
  10. Isidore, R., & Christie, P. (2018). Fundamental analysis versus technical analysis–A comparative review. International Journal of Recent Scientific Research, 9(1), 23009–23013. http://doi.org/10.24327/ijrsr.2018.0901.1380
  11. Jegadeesh, N. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation: Discussion. The Journal of Finance, 55(4), 1765–1770. http://www.jstor.org/stable/222378
  12. Kanojia, S., & Malhotra, D. (2021). A case study of stock market bubbles in the Indian stock market. Indian Journal of Finance, 15(2), 22–48. https://doi.org/10.17010/ijf/2021/v15i2/157638
  13. Li, G., & Zhu, J. (2014). Research on the effectiveness of technical indicators with the volume. Proceedings of the 2014 International Conference on Education, Management and Computing Technology (ICEMCT-14) (pp. 436–439). Atlantis Press. https://doi.org/10.2991/icemct-14.2014.105
  14. Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705–1765. https://doi.org/10.1111/0022-1082.00265
  15. Mehta, S. K., & Turan, M. S. (2008). Applicability of Sharpe's single index model in Indian security model. Indian Journal of Finance, 2(9), 32–38. https://www.indianjournalofentrepreneurship.com/index.php/IJF/article/view/71634
  16. Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. Penguin.
  17. Nagendra, S., Kumar, S., & Jayashree. (2018). Implications and usefulness of fundamental and technical analysis in stock market decision making. Indian Journal of Finance, 12(5), 54–71. https://doi.org/10.17010/ijf/2018/v12i5/123702
  18. Nti, I. K., Adekoya, A. F., & Weyori, B. A. (2020). A systematic review of fundamental and technical analysis of stock market predictions. Artificial Intelligence Review, 53(4), 3007–3057. https://doi.org/10.1007/s10462-019-09754-z
  19. Prasad, T. D., Chaitanya, C., & Thulasi Kumar, A. (2018). A study on stock's volatility in banking sector using technical analysis. International Research Journal of Engineering and Technology (IRJET), 5(1), 1016–1022.
  20. Pushpa, B. V., Sumithra, C. G., & Madhuri, H. (2017). Investment decision making using technical analysis: A study on select stocks in Indian stock market. IOSR Journal of Business and Management, 19(9), 24–33. http://dx.doi.org/10.9790/487X-1909062433
  21. Rakshith, L., & Manoj Kumara, N. V. (2018). Technical analysis on selected BSE stocks. International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), 7(7), 45–51. https://www.ijltemas.in/DigitalLibrary/Vol.7Issue7/45-51.pdf
  22. Sadhwani, R. (2019). Technical analysis of selected auto shares listed on Indian stock exchange. ELK Asia Pacific Journal of Finance and Risk Management, 10(4), 11–19. https://doi.org/10.16962/EAPJFRM/ISSN 0976-7185
  23. Singh, A. K., & Shrivastav, R. K. (2018). Evaluating the impact of the global financial crisis on the stock markets of BRICS countries. Indian Journal of Finance, 12(7), 7–27. https://doi.org/10.17010/ijf/2018/v12i7/129967
  24. Sudheer, V. (2015). Trading through technical analysis: An empirical study from Indian stock market. International Journal of Development Research, 5(8), 5410–5416. https://www.journalijdr.com/sites/default/files/issue-pdf/3916.pdf
  25. Vaiz, J. S., & Ramaswami, M. (2016). Forecasting stock trend using technical indicators with R. International Journal of Computational Intelligence and Informatics, 6(3), 206–219. https://www.periyaruniversity.ac.in/ijcii/issue/Vol6No3Dec2016/D4_PID0365.pdf
Editorial Scholar

Submit your Research to IJF

Submit your Manuscript → Author Guidelines