EVALUASI KINERJA STRATEGI FIBONACCI RETRACEMENT, MACD, DAN STRATEGI GABUNGAN MENGGUNAKAN BACKTESTING BERBASIS PYTHON PADA SAHAM LQ45 (2019–2024)

I Putu Precious Ananta Yohanes; Christimulia Purnama Trimurti; Gusti Ngurah Joko Adinegara; R. Tri Priyono Budi Santoso

doi:10.31539/dbr75s70

Authors

I Putu Precious Ananta Yohanes Universitas Dhyana Pura Bali
Christimulia Purnama Trimurti Universitas Dhyana Pura Bali
Gusti Ngurah Joko Adinegara Universitas Dhyana Pura Bali
R. Tri Priyono Budi Santoso Universitas Dhyana Pura Bali

DOI:

https://doi.org/10.31539/dbr75s70

Abstract

Penelitian ini mengevaluasi tiga strategi analisis teknikal—Fibonacci Retracement, Moving Average Convergence Divergence (MACD), dan strategi gabungan Fibonacci × MACD—menggunakan metode backtesting berbasis Python pada saham-saham indeks LQ45 periode 2019–2024. Data harga harian diperoleh dari Investing.com, dan seluruh sinyal entry dan exit dibentuk menggunakan aturan mekanis yang konsisten. Kinerja strategi dievaluasi menggunakan win rate, expectancy, R-multiple, total return, dan outperform rate. Hasil penelitian menunjukkan bahwa strategi gabungan memberikan performa paling unggul dengan win rate 60,58%, expectancy 0,586, dan outperform rate 64,96%. Integrasi antara struktur harga dan momentum terbukti meningkatkan kualitas sinyal, stabilitas performa, serta ketahanan strategi terhadap perubahan kondisi pasar. Penelitian ini menegaskan efektivitas pendekatan multi-konfirmasi sebagai kerangka analisis yang lebih stabil bagi trader pada pasar saham Indonesia.

References

Achelis, S. B. (2020). Technical analysis from A to Z (2nd ed.). McGraw-Hill.

Alkhatib, H., & Najjar, D. (2022). Evaluating the effectiveness of momentum indicators in emerging equity markets: Evidence from the Middle East. International Journal of Financial Studies, 10(3), 1–15. https://doi.org/10.3390/ijfs10030052

Appel, G. (1979). The moving average convergence divergence (MACD) method. Signalert Corporation.

Benjamin, A. T. (2015). Fibonacci numbers and the golden ratio. Princeton University Press.

Elder, A. (2014). The new trading for a living. Wiley.

Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55

Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M., Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P., Avila, D., Abdalla, S., & Willing, C. (2016). Jupyter Notebooks – A publishing format for reproducible computational workflows. In F. Loizides & B. Schmidt (Eds.), Positioning and power in academic publishing: Players, agents and agendas (pp. 87–90). IOS Press.

Krausz, R. (1998). Fibonacci applications and strategies for traders. Wiley.

McKinney, W. (2018). Python for data analysis: Data wrangling with pandas, NumPy, and IPython (2nd ed.). O’Reilly Media.

Mohanty, L. (2020). Mastering Fibonacci retracement in trading: A comprehensive guide. Fintech Press.

Pring, M. J. (2014). Technical analysis explained (5th ed.). McGraw-Hill.

Python Software Foundation. (2023). Python (Version 3.x) [Computer software]. https://www.python.org/

Rhee, H., & Kim, J. (2023). Multi-indicator confirmation strategies for trend continuation: Evidence from Asian equity markets. Journal of Technical Analysis and Quantitative Finance, 12(2), 45–63.

Sulastri, N., & Prabowo, A. (2021). Hybrid technical trading strategies and volatility resilience in Indonesia’s Islamic stock universe. Jurnal Ekonomi dan Keuangan Islam, 7(1), 25–39.

The pandas development team. (2020). pandas-dev/pandas (Version 1.x) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.3509134

van der Walt, S., Colbert, S. C., & Varoquaux, G. (2011). The NumPy array: A structure for efficient numerical computation. Computing in Science & Engineering, 13(2), 22–30. https://doi.org/10.1109/MCSE.2011.37

Wicaksono, R., & Puspita, D. (2020). The effectiveness of MACD indicator for LQ45 stocks during high volatility periods. Jurnal Pasar Modal Indonesia, 4(2), 101–115.

Zhao, T., & Wang, L. (2021). Trend structure and Fibonacci retracement effectiveness in Chinese mainland stock markets. China Finance Review International, 11(4), 589–605.