This study aims to determine the effectiveness of technical analysis in buying and selling decisions on the stocks of Indonesia’s four largest banks, namely PT Bank Central Asia Tbk. (BBCA), PT Bank Rakyat Indonesia (Persero) Tbk.
(BBRI), PT Bank Mandiri (Persero) Tbk. (BMRI), and PT Bank Negara Indonesia (Persero) Tbk. (BBNI). The research applies several widely used technical indicators, including Trendline, Support and Resistance, Simple Moving Average
(SMA), and Stochastic Oscillator, to analyze stock price movements during the period of May 2024 to December 2024.
This research uses a descriptive quantitative approach based on secondary
data obtained from Investing.com, TradingView, and the Indonesia Stock Exchange
(IDX). The analysis focuses on identifying market trends, momentum changes,
support and resistance zones, moving average crossovers, and divergence signals in
order to generate potential buy and sell indications.
The findings indicate that technical analysis can assist traders and investors
in identifying short-term market direction and improving trade timing decisions.
Trendline and Support-Resistance analysis were effective in identifying major
breakout and reversal areas, while the Simple Moving Average provided
confirmation of trend continuation and reversal through Golden Cross and Death
Cross signals. In addition, the Stochastic Oscillator proved useful in detecting
overbought and oversold conditions as well as bullish and bearish divergences that
often preceded price reversals.
The results also show that the four banking stocks experienced significant
trend changes throughout the observation period, particularly during the transition
from bullish conditions in mid-2024 to broader bearish pressure toward the end of
2024. Among the indicators used, the Stochastic Oscillator demonstrated stronger
responsiveness in identifying momentum shifts compared to the Simple Moving Average, which tended to lag price movement.
Overall, this study concludes that the combination of Trendline, Support and Resistance, Simple Moving Average, and Stochastic Oscillator can provide a more comprehensive framework for making trading decisions in the Indonesian banking sector. The study is expected to serve as a practical reference for investors, traders, and future researchers interested in technical analysis within emerging financial markets.