A Comparative study between returns on RSI and Stochastic RSI using the Buy and Hold Strategy on Indian Equities
Main Article Content
Abstract
The research will focus on trying to establish the better returns on Stochastic RSI in comparison to Relative Strength Index. The study puts technical trading indicators in context of financial econometrics, performance analysis via accounting, to fill the gap between market-based indicators, on the one hand, and theoretical models of predictability of returns in finance, on the other. The hindrance on the way is the absence of evident research on what indicator gathers more effectively.
Design, Methodology and Approach:
With the help of hypothesis testing supported by python we test the performance of 23 equities of various sectors to determine whether the returns on the 23 equities combined outperform the lagging Relative Strength Index with the help of the StochasticRSI. At the same time we also can test the performance of the two indicators on the said equities in order to know whether a selectively pointed approach gives us an outcome in which we can know what indicator to use on what equity.
Findings:
The study gives tangible understanding of the performance of the indicators and assists in advising which indicator to trade which equity in order to get better returns. We are able to determine the equities that StochasticRSI is performing better than RSI. We also determine performance of StochasticRSI v/s RSI performance on sample we are testing.
Research Limitations:
Trading costs have not been included. With these costs in mind, we will have a better picture. The sample is small and does not work on the whole universe of equities in Indian Equity Market.
Article Details
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References
1. Ball, R., & Brown, P. (2013). An empirical evaluation of accounting income numbers. In Financial Accounting and Equity Markets (pp. 27-46). Routledge.
2. Beaver, W. H., McNichols, M. F., & Wang, Z. Z. (2018). The information content of earnings announcements: new insights from intertemporal and cross-sectional behavior. Review of Accounting Studies, 23(1), 95-135.
3. Bessembinder, H., & Chan, K. (1995). The profitability of technical trading rules in the Asian stock markets ". In Pacific-Basin Finance Journal (Vol. 3).
4. Chong, T. T. L., & Ip, H. T. S. (2009). Do momentum-based strategies work in emerging currency markets? Pacific Basin Finance Journal, 17(4), 479–493.
https://doi.org/10.1016/j.pacfin.2008.11.002
5. Chong, T. T. L., & Ng, W. K. (2008). Technical analysis and the London stock exchange: Testing the MACD and RSI rules using the FT30. Applied Economics Letters, 15(14), 1111–1114. https://doi.org/10.1080/13504850600993598
6. Cohen, G., & Cabiri, E. (2015). Can technical oscillators outperform the buy and hold strategy? Applied Economics, 47(30), 3189–3197. https://doi.org/10.1080/00036846.2015.1013609
7. Dahiya, S. B. (Shri B. (2000). The current state of business disciplines. Spellbound Publications.
8. Dimson, E., & Mussavian, M. (1998). A brief history of market efficiency. In European Financial Management (Vol. 4, Issue 1).
9. Dsouza, J., Mallikarjunappa, T., & Dsouza, J. J. (2013). A Study of Semi-Strong Form of Market Efficiency of Indian Stock Market. https://www.researchgate.net/publication/317017352
10. Elaine Cherop, L. (2020). Application Of Technical Analysis In The Forex Market: Comparison Of Technical Trading Rules In Developed And Emerging Markets.
11. Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of financial economics, 33(1), 3-56.
12. Gunasekarage, A., & Power, D. M. (2001). The profitability of moving average trading rules in South Asian stock markets.
13. Jensen, M. C., & Benington, G. A. (1970). Random Walks and Technical Theories: Some Additional Evidence. In Source: The Journal of Finance (Vol. 25, Issue 2).
14. Kim Man Lui, T. T. L. C. (2013). Do technical Analysis outperform Novice traders.
15. Kumar, L. (2017). Market efficiency in India: an empirical study of random walk hypothesis of Indian stock market–NSE midcap. Available at SSRN 3078089.
https://doi.org/10.2139/ssrn.3078089
16. Kwon, K. Y., & Kish, R. J. (2002). Technical trading strategies and return predictability: NYSE. Applied Financial Economics, 12(9), 639–653. https://doi.org/10.1080/09603100010016139
17. Macedo, L. L., Godinho, P., & Alves, M. J. (2020). A comparative study of technical trading strategies using a genetic algorithm. Computational Economics, 55(1), 349-381.
18. Majumdar, A., & Chakrabarty, A. (n.d.). The Effectiveness and Sensitivity of Stochastic Oscillator and Relative Strength Index in Select Indian Stocks Technical Analysis View project The Effectiveness and Sensitivity of Stochastic Oscillator and Relative Strength Index in Select Indian Stocks. https://www.researchgate.net/publication/354582793
19. Menkhoff, L. (2010). The use of technical analysis by fund managers: International evidence. Journal of Banking & Finance, 34(11), 2573–2586. https://doi.org/10.1016/J.JBANKFIN.2010.04.014
20. Murphy, J. J. (1999). John J Murphy - Technical Analysis Of The Financial Markets.
21. Murphy, J. J. . (2000). Technical analysis of the financial markets. Shin Won Agency Co.
22. Naved, M., & Srivastava, P. (n.d.). Profitability of Oscillators used in Technical Analysis for Financial Market. 2(9), 925–931.
http://www.krishisanskriti.org/aebm.html
23. Neftci, S. N. (1991). Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of “Technical Analysis.” In Source: The Journal of Business (Vol. 64, Issue 4). https://www.jstor.org/stable/2353293
24. Petrusheva, N., & Jordanoski, I. (2016). COMPARATIVE ANALYSIS BETWEEN THE FUNDAMENTAL AND TECHNICAL ANALYSIS OF STOCKS. In JPMNT) Journal of Process Management-New Technologies, International (Vol. 4, Issue 2). www.japmnt.com
25. Rosillo, R., de la Fuente, D., & 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, 45(12), 1541–1550. https://doi.org/10.1080/00036846.2011.631894
26. Shik, T. C., & Chong, T. T. L. (2007). A comparison of MA and RSI returns with exchange rate intervention. Applied Economics Letters, 14(5), 371–383. https://doi.org/10.1080/13504850500426269
27. Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. In Source: The Journal of Finance (Vol. 54, Issue 5).
28. Tanaka-Yamawaki, M., & Tokuoka, S. (2007). Adaptive use of technical indicators for the prediction of intra-day stock prices. Physica A: Statistical Mechanics and Its Applications, 383(1 SPEC. ISS.), 125–133.
https://doi.org/10.1016/j.physa.2007.04.126
29. TREYNOR, J. L., & FERGUSON, R. (1985). In Defense of Technical Analysis. The Journal of Finance, 40(3), 757–773.
https://doi.org/10.1111/j.1540-6261.1985.tb05000.
30. Tsinaslanidis, P. (2014). Perceptually important points and dynamic time warping in time series prediction: Application to finance MASTER THESIS.