Analisis Pola Candlestick dalam Memprediksi Tren Saham pada Perusahaan Non-Bank Financial Institutions (NBFIs) Terdaftar di Indeks LQ45 Periode 2019–2025
DOI:
https://doi.org/10.55606/cemerlang.v6i3.9655Keywords:
Candlestick Patterns, LQ45 Index, Reversal, Stock Trends, Technical AnalysisAbstract
This study aims to analyze the use of Candlestick patterns as a tool for predicting stock price trends in Non-Bank Financial Institutions (NBFIs) companies listed on the LQ45 Index for the 2019 - 2025 period, and to evaluate their effectiveness and role in investment decision-making amid market volatility. This study uses a descriptive quantitative approach to eight issuers from four sectors, namely Industrials, Consumer Non-Cyclicals, Healthcare, and Telecommunications, with secondary data in the form of daily Open, high, low, and Close (OHLC) prices from Investing.com. The analysis was conducted using descriptive statistics and mode to identify the most dominant Bullish Reversal and Bearish Reversal Candlestick patterns. The results found 348 Bullish Reversal patterns and 429 Bearish Reversal patterns, with Bullish Harami, Bullish Engulfing, and Morning Star as the most frequent Bullish patterns, and Evening Star as the most dominant Bearish pattern. All issuers showed a dominance of Bearish Reversal patterns, indicating stronger selling pressure during the study period due to the Covid-19 pandemic, rising global interest rates, and economic slowdown. These findings confirm that Candlestick patterns remain relevant as a technical analysis tool for detecting potential reversals of stock trends in the Indonesian capital market, especially when combined with other technical indicators.
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References
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Sage Publications.
Dow, C. H. (1960). New England journalist highlights in the newspaper career. Finance, 33(11). https://doi.org/10.2307/3111780
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486
Harori, M. I., & Sobita, N. E. (2023). Investasi dan pasar modal administrasi bisnis. Nesqi Internasional Indonesia.
Kurniawan, D., Rahmah, M., & Azzahra, Z. B. (2025). Analisis pengaruh investasi pasar saham terhadap pertumbuhan ekonomi di Indonesia. Pediaqu: Jurnal Pendidikan Sosial dan Humaniora, 4(2), 2572–2581. https://doi.org/10.63607/jcmb.v13i3.37
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
Lorena, A., Preciado, J., & Nacional, I. P. (2019). Huelum trading system: A low-frequency algorithm proposal, 651–669. https://doi.org/10.21919/remef.v14i4.435
Mersal, E. R., Karaoglan, K. M., & Kutucu, H. (2025). Enhancing market trend prediction using convolutional neural networks on Japanese candlestick patterns. PeerJ Computer Science, 11, 1–38. https://doi.org/10.7717/peerj-cs.2719
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Nison, S. (2001). Japanese candlestick charting techniques: A contemporary guide to the ancient investment techniques of the Far East (2nd ed.).
Pring, M. J. (2002). Technical analysis explained: The successful investor's guide to spotting investment trends and turning points (4th ed.). McGraw-Hill.
Sani, N., & Paramita, V. S. (2024). Literasi keuangan sebagai variabel moderasi (Studi pada investor Generasi Z Jawa Barat). Equilibrium, 13(1), 134–147. https://doi.org/10.35906/equili.v13i1.1886
Setiawan, K., Tristiyanto, & Irawati, A. R. (2021). Sistem analisis rekomendasi saham pada indeks LQ45 menggunakan indikator Moving Average Convergence Divergence (MACD) dan Relative Strength Index (RSI). Jurnal Komputasi Unila, 9(2), 50–59. https://doi.org/10.23960/komputasi.v9i2.2870
Sopacua, Januarga, Andhini, & Michaell. (2025). Analisis tingkat risiko dan pengembalian saham pada indeks LQ45 sektor industri manufaktur. International Journal of Economics and Strategic Management (IJESM), 3(1).
Sugiyono. (2019). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.
Tharavanij, P., Siraprapasiri, V., & Rajchamaha, K. (2017). Profitability of candlestick charting patterns in the Stock Exchange of Thailand. SAGE Open, 7(4). https://doi.org/10.1177/2158244017736799
Wang, J., Li, X., Jia, H., Peng, T., & Tan, J. (2022). Predicting stock market volatility from candlestick charts: A multiple attention mechanism graph neural network approach. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/4743643
Wardhana, C. S. (2024). Eksplorasi fundamental cryptocurrency dalam volatilitas harga. Jurnal Ilmiah Ekonomi dan Bisnis, 5(4). https://doi.org/10.46799/jsa.v5i4.1094
Wicaksono, S. R., Setiawan, R., & Purnomo. (2022). Candlestick pattern research analysis, future and beyond: A systematic literature review using PRISMA. Journal of Computer Science and Technology Studies, 4(2), 157–164. https://doi.org/10.32996/jcsts.2022.4.2.19
Wijaya, B., Karsianto, W. S., & Nur, T. (2023). The impact of COVID-19 related news to stock performance on pre-crisis, crisis, and post-crisis: Study case in Indonesia's finance sector and SRI-KEHATI index. E3S Web of Conferences, 426. https://doi.org/10.1051/e3sconf/202342601042
Wulandari, J., Wardianto, K. B., Suripto, & Efendi, N. (2023). Peningkatan pengetahuan investasi di pasar modal pada komunitas muda Yasmin. GERVASI: Jurnal Pengabdian kepada Masyarakat, 7(3), 1057–1066. https://doi.org/10.31571/gervasi.v7i3.6308
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