Analysis of Optimal Stock Returns in the Banking Sector Using Stochastic RSI, MACD, and Bollinger Bands Indicators
DOI:
https://doi.org/10.54099/hbr.v6i2.1956Keywords:
Keywords: Technical Analysis, Stochastic RSI, MACD, Bollinger Bands, Geometric Mean, Stock Return, Banking Sector, LQ45 Index.Abstract
Purpose – This study aims to examine the differences in stock returns generated by the Stochastic Relative Strength Index (Stochastic RSI), Moving Average Convergence Divergence (MACD), and Bollinger Bands indicators and to determine the optimal return for banking sector stocks included in the LQ45 Index during the period from March 2023 to February 2026 using the Geometric Mean method. Methodology/Approach – This study employed a descriptive quantitative research design. Secondary data consisting of daily closing prices of five banking sector stocks listed in the LQ45 Index were collected from the Stockbit platform. Buy and sell signals were generated using the Stochastic RSI, MACD, and Bollinger Bands indicators. The resulting stock returns were analyzed using descriptive statistics, normality and homogeneity tests, and the Kruskal–Wallis nonparametric test. The Geometric Mean method was subsequently applied to determine the optimal investment return. Findings – The results revealed a statistically significant difference in stock returns among the three technical indicators (Asymp. Sig. = 0.000; p < 0.05). Based on the Mean Rank values, the Stochastic RSI demonstrated the highest effectiveness in generating stock returns, followed by Bollinger Bands and MACD. The Geometric Mean analysis indicated that the Bollinger Bands–BBTN combination produced the highest optimal return of 7.31%, while BBNI generated the highest return under the Stochastic RSI indicator at 6.34%. Overall, BBTN and BBNI exhibited superior investment performance compared with the other banking stocks included in the analysis. Novelty/Value – This study contributes to the technical analysis literature by simultaneously comparing the performance of three widely used technical indicators and evaluating their optimal returns using the Geometric Mean method. The findings provide empirical evidence that may assist investors in selecting the most appropriate technical indicator based on the characteristics of banking sector stocks, thereby supporting more effective investment decision making.
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