Comparison of MACD and Stochastic in Optimizing Stock Investment Strategy
Abstract
The Purpose of study is to analyze the accuracy level and compare the profit levels generated using the Moving Average Convergence Divergence (MACD) and Stochastic Oscillator (SO) indicators through a comparative quantitative approach. The analysis is conducted to observe the performance differences between the two indicators in optimizing profits on IDX30 stocks. The Wilcoxon test performed to examine this comparison indicates a significant difference in the accuracy level and profit level generated between the two indicators. The results of this study show that there is a significant difference in the accuracy levels of the MACD and Stochastic indicators in optimizing profits. This is due to the fact that the MACD indicator tends to be slow in responding to price changes, especially in volatile market conditions. Additionally, the MACD indicator mostly generates false signals at a rate of 60%, while the Stochastic indicator predominantly produces true signals at a rate of 93%. The findings of this study also indicate a significant difference in the profit levels generated using the MACD and Stochastic indicators, with the Stochastic indicator being more optimal in generating profits. This is because the MACD indicator is classified as a lagging technical indicator, while the Stochastic indicator is considered a leading technical indicator. The results of this research can serve as a consideration in making decisions to buy or sell stocks.
Keywords: Accuracy; Profit Optimization; MACD; Stochastic
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References
Agudelo Aguirre, A. A., Duque Méndez, N. D., & Rojas Medina, R. A. (2021). Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator. Journal of Economics, Finance and Administrative Science, 26(52), 268–281. https://doi.org/10.1108/JEFAS-06-2020-0203
Agusta, I. M. A. I., Barakbah, A., & Fariza, A. (2022). Technical Analysis Based Automatic Trading Prediction System for Stock Exchange using Support Vector Machine. EMITTER International Journal of Engineering Technology, 10(2), 279–293. https://doi.org/10.24003/emitter.v10i2.740
Ali, A., Shah, A., Khan, A. H., Sharif, M. U., Zahid, Z. U., Shahid, R., Jan, T., & Zafar, M. H. (2024). Speed vs. efficiency: A framework for high-frequency trading algorithms on FPGA using Zynq SoC platform. Alexandria Engineering Journal, 96(August 2023), 1–14. https://doi.org/10.1016/j.aej.2024.03.064
Allen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51(2), 245–271. https://doi.org/10.1016/S0304-405X(98)00052-X
Anghel, G. D. I. (2015). Stock Market Efficiency and the MACD. Evidence from Countries around the World. Procedia Economics and Finance, 32(15), 1414–1431. https://doi.org/10.1016/s2212-5671(15)01518-x
Astawa, I. G. C. A., & Suaryana, I. G. N. A. (2024). Market Reaction To the Enactment of Finance Minister Regulation Number 120 of 2023 on Property and Real Estate Stocks. Transekonomika: Akuntansi, Bisnis Dan Keuangan, 4(5), 636–653. https://doi.org/10.55047/transekonomika.v4i5.706
Bhukkavesa, K., & Sakunasingha, B. (2018). Effectiveness of Investment Strategies Based on MACD Indikator: Evidence From The Stock Exchange of Thailand. Journal of Global Business Review, 20(1), 1–12.
Bisoi, R., & Dash, P. K. (2014). A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter. Applied Soft Computing Journal, 19, 41–56. https://doi.org/10.1016/j.asoc.2014.01.039
Brock, W., Lakonishok, J., & Lebaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731–1764. https://doi.org/10.1111/j.1540-6261.1992.tb04681.x
Cynthia Dewi. (2018). Tingkat Akurasi Indikator Analisis Teknikal dalam Menentukan Sinyal Jual dan Sinyal Beli Saham Pada Perusahaan Sub Sektor Kontruksi Bangunan yang Terdaftar di BEI Periode 2013-2017. In Nucleic Acids Research (Vol. 6, Issue 1). http://dx.doi.org/10.1016/j.gde.2016.09.008%0A
Dewi, K. S., & Yasa, G. W. (2020). The Effects of Executive and Company Characteristics on Tax Aggressiveness. Jurnal Ilmiah Akuntansi Dan Bisnis, 15(2), 280. https://doi.org/10.24843/jiab.2020.v15.i02.p10
Farias Nazário, R. T., e Silva, J. L., Sobreiro, V. A., & Kimura, H. (2017). A literature review of technical analysis on stock markets. Quarterly Review of Economics and Finance, 66, 115–126. https://doi.org/10.1016/j.qref.2017.01.014
Haanurat, D. A. I., Arman, A., & Nur’aeni, N. (2022). Analisis Moving Average Convergence Divergence pada Investasi Saham Syariah saat New Era. Ekombis Sains: Jurnal Ekonomi, Keuangan Dan Bisnis, 7(1), 1–10. https://doi.org/10.24967/ekombis.v7i1.1540
Hartono, J., & Sulistiawan, D. (2014). The market quality to technical analysis performance: Intercountry analysis. Gadjah Mada International Journal of Business, 16(3), 243–254. https://doi.org/10.22146/gamaijb.5658
Herlambang, M. Y., Kusuma, P. J., Usman, U., & Waluyo, D. E. (2024). Analisis Teknikal Saham Energi Menggunakan Indikator Macd Dan Indikator Rsi Pada Indeks Lq45. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 8(2), 187–206. https://doi.org/10.31955/mea.v8i2.4021
John Grue, B. oksendal. (1997). A stochastic oscilator with time-dependent damping. 4149(June 1996).
Kang, B. K. (2021). Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market. Journal of Risk and Financial Management, 14(1). https://doi.org/10.3390/jrfm14010037
Kang, B. K. (2023). Optimal and Non-Optimal MACD Parameter Values and Their Ranges for Stock-Index Futures: A Comparative Study of Nikkei, Dow Jones, and Nasdaq. J. Risk Financial Management, 16. https://doi.org/10.3390/jrfm16120508
Krzysztof Borowski, I. P.-G. (2019). optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange. Bank i Kredyt.
Liu, X. L. (2019). Stochastic process and its role in the development of the financial market: Celebrating professor chows long and successful career. Communications on Stochastic Analysis, 13(3–4), 403–411. https://doi.org/10.31390/cosa.13.3.07
Logambal, R., & Kanagasabapathy, G. (2024). Investment Decision Using Technical Analysis: A Study on Selected Stocks in Indian Stock Market. Shanlax International Journal of Economics, 12(2), 62–68. https://doi.org/10.34293/economics.v12i2.7059
Magui, A., Elsiefy, E., & Bahaa, M. (2023). The Impact of Technical Analysis on Investors’ Financial Decisions in an Emerging Market: Evidence from the Egyptian Stock Market. American Journal of Industrial and Business Management, 13(10), 1123–1151. https://doi.org/10.4236/ajibm.2023.1310063
Markus, L., & Weerasinghe, A. (1988). Stochastic oscillators. Journal of Differential Equations, 71(2), 288–314. https://doi.org/10.1016/0022-0396(88)90029-0
Nabiilah, I. A., Hartono, U., & Haryono, N. A. (2024). Analisis Kointegrasi Indeks Saham Filipina Psei, Indeks Saham Malaysia Klci, Indeks Saham As Djia Dan Variabel Makroekonomi Dengan Ihsg. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 8(1), 528–557. https://doi.org/10.31955/mea.v8i1.3740
Narti Eka Putri, & Hardiansyah, A. (2023). Perbandingan Indikator Stochastic Oscillator Dan Moving Average Convergence Divergence Dalam Optimalisasi Profit Pada Saham Sub Sektor Perbankan Di Idx 30. Journal of Management Studies, 17(2), 53–54.
Nasih, A. C., & Ridloah, S. (2021). Analisis Komparasi Penggunaan Metode MACD, Moving Average, dan Stochastic dalam Optimalisasi Profit. Jurnal Pasar Modal Dan Bisnis, 3(1), 123–132. https://doi.org/10.37194/jpmb.v3i1.61
Neely, M. J. (2010). Stock market trading via stochastic network optimization. Proceedings of the IEEE Conference on Decision and Control, 2777–2784. https://doi.org/10.1109/CDC.2010.5717310
Neftci, S. N. (1991). Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of “Technical Analysis.” In The Journal of Business (Vol. 64, Issue 4, p. 549). https://doi.org/10.1086/296551
Nguyen, D. T., & Nguyen, S. L. (2019). Euler-Maruyama method for regime switching stochastic differential equations with holder coefficients. Communications on Stochastic Analysis, 13(3–4), 323–356. https://doi.org/10.31390/cosa.13.3.04
Nguyen, N. N., & Yin, G. (2019). Stochastic Partial Differential Equation SIS Epidemic Models: Modeling and Analysis. Communications on Stochastic Analysis, 13(3). https://doi.org/10.31390/cosa.13.3.08
Nurcahyo, A. D., & Susliyanti, E. D. (2024). Uji Beda Keputusan Sinyal Jual Beli Saham Sebelum dan Sesudah Menggunakan Teknik Moving Average Convergence Divergence (MACD) dan Stochastic Oscillator (SO). Reslaj: Religion Education Social Laa Roiba Journal, 6(6), 3060–3074. https://doi.org/10.47476/reslaj.v6i6.2268
Paik, C. K., Choi, J., & Vaquero, I. U. (2024). Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and William%R: A Case Study on the U.S. and Korean Indices. Journal of Risk and Financial Management, 17(3). https://doi.org/10.3390/jrfm17030092
Pramudya Rommy, I. S. (2020). Finance & Banking Studies Efficiency of Technical Analysis for the Stock Trading. 9(1).
Putra, A. S., & Miharja, R. (2023). Technical Analysis in Companies Listed on Lq45 on the Indonesia Stock Exchange 2011–2018. Ultima Management : Jurnal Ilmu Manajemen, 15(1), 124–130. https://doi.org/10.31937/manajemen.v15i1.3175
R, P., & A, D. M. (2024). A Study On The Effectiveness Of Moving Average Convergence And Divergence (MACD). Educational Administration: Theory and Practice, 30(5), 8609–8618. https://doi.org/10.53555/kuey.v30i5.3518
Rahmadani, N. A. (2024). Kebangkrutan Silicon Valley Bank : Analisis Return Saham Menggunakan Indikator Stochastic. 7(1), 106–114. https://doi.org/10.35326/jiam.v7i1.5055
Regi Kumar, M. (2023). Optimization of Trading Strategies on Indian Stock Market System using Moving Average Convergence Divergence ( MACD ) Indicator. The International Conference on Emerging Trends in Engineering Yukthi, April, 10–12.
Reswita, Y., Nanda, N., & Rahmadani, Y. (2022). Analisis Keakuratan Moving Average Convergence Divergence Dan Stochostic Oscillator Pada Perusahaan Sub Sektor Perbankan Yang Terdaftar Di Bursa Efek Indonesia (Bei). Menara Ilmu, 16(2), 117–125. https://doi.org/10.31869/mi.v16i2.3440
Risaldi, M., Haanurat, A. I., & Jaya, A. (2024). Prediksi Pergerakan Saham Menggunakan William Fraktal dan Moving Average ( Studi Pada Saham Sektor Industri Pertambangan di Bursa Efek Indonesia ). Jurnal Riset Ilmu Ekonomi.
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
Rosyidah, N., & Hafi, R. U. (2021). Analisa Teknikal MACD, RSI, SO, dan Buy and Hold untuk Mencapai Return Optimal Saham JII30 di Bursa Efek Indonesia. Jurnal Pasar Modal Dan Bisnis, 3(1), 75–88. https://doi.org/10.37194/jpmb.v3i1.66
Santoso, A. A., & Sukamulja, S. (2020). Penggunaan Kombinasi Indikator Sma, Ema, Macd, Rsi, Dan Mfi Untuk Menentukan Keputusan Beli Dan Jual Pada Saham-Saham Di Sektor Lq45 Bei Tahun 2018. Modus, 32(2), 159–174. https://doi.org/10.24002/modus.v32i2.3519
Simbolon, T. G. (2024). Data Jumlah Investor Pasar Modal di Indonesia hingga Februari 2024. DataIndonesia.Id.
Smith, D. M., Fauger̀e, C., & Wang, Y. (2013). Head head and shoulders above the rest the performance of institutional portfolio managers who use technical analysis. Research in Finance, 29, 167–189. https://doi.org/10.1108/S0196-3821(2013)0000029010
Suryanto, S. (2021). Analisis Teknikal Dengan Menggunakan Moving Average Convergence-Divergence Dan Relative Strength Index Pada Saham Perbankan. Jurnal Ilmu Keuangan Dan Perbankan (JIKA), 11(1), 51–65. https://doi.org/10.34010/jika.v11i1.5896
Tika Denisa Simanjuntak, Isfenti Sadalia, & Nisrul Irawati. (2023). Technical Analysis As the Basis for Decision Making in Stock Investment in Pt. Bank Mestika Dharma.Tbk in the Indonesian Capital Market (During the Covid Pandemic January 2020 - June 2021). International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS), 3(5), 1474–1490. https://doi.org/10.54443/ijebas.v3i5.1085
Tiovandi, M. R. (2024). Anailisis Dengan Indikator Bollinger Band dan Stochastic Oscillator Pada Saham Serta Fundamental Perusahaan LQ 45 Sub Sektor Perbankan. 1(6), 249–257.
Wang, J., & Kim, J. (2018). Predicting stock price trend using MACD optimized by historical volatility. Mathematical Problems in Engineering, 2018. https://doi.org/10.1155/2018/9280590
Agusta, I. M. A. I., Barakbah, A., & Fariza, A. (2022). Technical Analysis Based Automatic Trading Prediction System for Stock Exchange using Support Vector Machine. EMITTER International Journal of Engineering Technology, 10(2), 279–293. https://doi.org/10.24003/emitter.v10i2.740
Ali, A., Shah, A., Khan, A. H., Sharif, M. U., Zahid, Z. U., Shahid, R., Jan, T., & Zafar, M. H. (2024). Speed vs. efficiency: A framework for high-frequency trading algorithms on FPGA using Zynq SoC platform. Alexandria Engineering Journal, 96(August 2023), 1–14. https://doi.org/10.1016/j.aej.2024.03.064
Allen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial Economics, 51(2), 245–271. https://doi.org/10.1016/S0304-405X(98)00052-X
Anghel, G. D. I. (2015). Stock Market Efficiency and the MACD. Evidence from Countries around the World. Procedia Economics and Finance, 32(15), 1414–1431. https://doi.org/10.1016/s2212-5671(15)01518-x
Astawa, I. G. C. A., & Suaryana, I. G. N. A. (2024). Market Reaction To the Enactment of Finance Minister Regulation Number 120 of 2023 on Property and Real Estate Stocks. Transekonomika: Akuntansi, Bisnis Dan Keuangan, 4(5), 636–653. https://doi.org/10.55047/transekonomika.v4i5.706
Bhukkavesa, K., & Sakunasingha, B. (2018). Effectiveness of Investment Strategies Based on MACD Indikator: Evidence From The Stock Exchange of Thailand. Journal of Global Business Review, 20(1), 1–12.
Bisoi, R., & Dash, P. K. (2014). A hybrid evolutionary dynamic neural network for stock market trend analysis and prediction using unscented Kalman filter. Applied Soft Computing Journal, 19, 41–56. https://doi.org/10.1016/j.asoc.2014.01.039
Brock, W., Lakonishok, J., & Lebaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731–1764. https://doi.org/10.1111/j.1540-6261.1992.tb04681.x
Cynthia Dewi. (2018). Tingkat Akurasi Indikator Analisis Teknikal dalam Menentukan Sinyal Jual dan Sinyal Beli Saham Pada Perusahaan Sub Sektor Kontruksi Bangunan yang Terdaftar di BEI Periode 2013-2017. In Nucleic Acids Research (Vol. 6, Issue 1). http://dx.doi.org/10.1016/j.gde.2016.09.008%0A
Dewi, K. S., & Yasa, G. W. (2020). The Effects of Executive and Company Characteristics on Tax Aggressiveness. Jurnal Ilmiah Akuntansi Dan Bisnis, 15(2), 280. https://doi.org/10.24843/jiab.2020.v15.i02.p10
Farias Nazário, R. T., e Silva, J. L., Sobreiro, V. A., & Kimura, H. (2017). A literature review of technical analysis on stock markets. Quarterly Review of Economics and Finance, 66, 115–126. https://doi.org/10.1016/j.qref.2017.01.014
Haanurat, D. A. I., Arman, A., & Nur’aeni, N. (2022). Analisis Moving Average Convergence Divergence pada Investasi Saham Syariah saat New Era. Ekombis Sains: Jurnal Ekonomi, Keuangan Dan Bisnis, 7(1), 1–10. https://doi.org/10.24967/ekombis.v7i1.1540
Hartono, J., & Sulistiawan, D. (2014). The market quality to technical analysis performance: Intercountry analysis. Gadjah Mada International Journal of Business, 16(3), 243–254. https://doi.org/10.22146/gamaijb.5658
Herlambang, M. Y., Kusuma, P. J., Usman, U., & Waluyo, D. E. (2024). Analisis Teknikal Saham Energi Menggunakan Indikator Macd Dan Indikator Rsi Pada Indeks Lq45. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 8(2), 187–206. https://doi.org/10.31955/mea.v8i2.4021
John Grue, B. oksendal. (1997). A stochastic oscilator with time-dependent damping. 4149(June 1996).
Kang, B. K. (2021). Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market. Journal of Risk and Financial Management, 14(1). https://doi.org/10.3390/jrfm14010037
Kang, B. K. (2023). Optimal and Non-Optimal MACD Parameter Values and Their Ranges for Stock-Index Futures: A Comparative Study of Nikkei, Dow Jones, and Nasdaq. J. Risk Financial Management, 16. https://doi.org/10.3390/jrfm16120508
Krzysztof Borowski, I. P.-G. (2019). optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange. Bank i Kredyt.
Liu, X. L. (2019). Stochastic process and its role in the development of the financial market: Celebrating professor chows long and successful career. Communications on Stochastic Analysis, 13(3–4), 403–411. https://doi.org/10.31390/cosa.13.3.07
Logambal, R., & Kanagasabapathy, G. (2024). Investment Decision Using Technical Analysis: A Study on Selected Stocks in Indian Stock Market. Shanlax International Journal of Economics, 12(2), 62–68. https://doi.org/10.34293/economics.v12i2.7059
Magui, A., Elsiefy, E., & Bahaa, M. (2023). The Impact of Technical Analysis on Investors’ Financial Decisions in an Emerging Market: Evidence from the Egyptian Stock Market. American Journal of Industrial and Business Management, 13(10), 1123–1151. https://doi.org/10.4236/ajibm.2023.1310063
Markus, L., & Weerasinghe, A. (1988). Stochastic oscillators. Journal of Differential Equations, 71(2), 288–314. https://doi.org/10.1016/0022-0396(88)90029-0
Nabiilah, I. A., Hartono, U., & Haryono, N. A. (2024). Analisis Kointegrasi Indeks Saham Filipina Psei, Indeks Saham Malaysia Klci, Indeks Saham As Djia Dan Variabel Makroekonomi Dengan Ihsg. Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA), 8(1), 528–557. https://doi.org/10.31955/mea.v8i1.3740
Narti Eka Putri, & Hardiansyah, A. (2023). Perbandingan Indikator Stochastic Oscillator Dan Moving Average Convergence Divergence Dalam Optimalisasi Profit Pada Saham Sub Sektor Perbankan Di Idx 30. Journal of Management Studies, 17(2), 53–54.
Nasih, A. C., & Ridloah, S. (2021). Analisis Komparasi Penggunaan Metode MACD, Moving Average, dan Stochastic dalam Optimalisasi Profit. Jurnal Pasar Modal Dan Bisnis, 3(1), 123–132. https://doi.org/10.37194/jpmb.v3i1.61
Neely, M. J. (2010). Stock market trading via stochastic network optimization. Proceedings of the IEEE Conference on Decision and Control, 2777–2784. https://doi.org/10.1109/CDC.2010.5717310
Neftci, S. N. (1991). Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of “Technical Analysis.” In The Journal of Business (Vol. 64, Issue 4, p. 549). https://doi.org/10.1086/296551
Nguyen, D. T., & Nguyen, S. L. (2019). Euler-Maruyama method for regime switching stochastic differential equations with holder coefficients. Communications on Stochastic Analysis, 13(3–4), 323–356. https://doi.org/10.31390/cosa.13.3.04
Nguyen, N. N., & Yin, G. (2019). Stochastic Partial Differential Equation SIS Epidemic Models: Modeling and Analysis. Communications on Stochastic Analysis, 13(3). https://doi.org/10.31390/cosa.13.3.08
Nurcahyo, A. D., & Susliyanti, E. D. (2024). Uji Beda Keputusan Sinyal Jual Beli Saham Sebelum dan Sesudah Menggunakan Teknik Moving Average Convergence Divergence (MACD) dan Stochastic Oscillator (SO). Reslaj: Religion Education Social Laa Roiba Journal, 6(6), 3060–3074. https://doi.org/10.47476/reslaj.v6i6.2268
Paik, C. K., Choi, J., & Vaquero, I. U. (2024). Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and William%R: A Case Study on the U.S. and Korean Indices. Journal of Risk and Financial Management, 17(3). https://doi.org/10.3390/jrfm17030092
Pramudya Rommy, I. S. (2020). Finance & Banking Studies Efficiency of Technical Analysis for the Stock Trading. 9(1).
Putra, A. S., & Miharja, R. (2023). Technical Analysis in Companies Listed on Lq45 on the Indonesia Stock Exchange 2011–2018. Ultima Management : Jurnal Ilmu Manajemen, 15(1), 124–130. https://doi.org/10.31937/manajemen.v15i1.3175
R, P., & A, D. M. (2024). A Study On The Effectiveness Of Moving Average Convergence And Divergence (MACD). Educational Administration: Theory and Practice, 30(5), 8609–8618. https://doi.org/10.53555/kuey.v30i5.3518
Rahmadani, N. A. (2024). Kebangkrutan Silicon Valley Bank : Analisis Return Saham Menggunakan Indikator Stochastic. 7(1), 106–114. https://doi.org/10.35326/jiam.v7i1.5055
Regi Kumar, M. (2023). Optimization of Trading Strategies on Indian Stock Market System using Moving Average Convergence Divergence ( MACD ) Indicator. The International Conference on Emerging Trends in Engineering Yukthi, April, 10–12.
Reswita, Y., Nanda, N., & Rahmadani, Y. (2022). Analisis Keakuratan Moving Average Convergence Divergence Dan Stochostic Oscillator Pada Perusahaan Sub Sektor Perbankan Yang Terdaftar Di Bursa Efek Indonesia (Bei). Menara Ilmu, 16(2), 117–125. https://doi.org/10.31869/mi.v16i2.3440
Risaldi, M., Haanurat, A. I., & Jaya, A. (2024). Prediksi Pergerakan Saham Menggunakan William Fraktal dan Moving Average ( Studi Pada Saham Sektor Industri Pertambangan di Bursa Efek Indonesia ). Jurnal Riset Ilmu Ekonomi.
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
Rosyidah, N., & Hafi, R. U. (2021). Analisa Teknikal MACD, RSI, SO, dan Buy and Hold untuk Mencapai Return Optimal Saham JII30 di Bursa Efek Indonesia. Jurnal Pasar Modal Dan Bisnis, 3(1), 75–88. https://doi.org/10.37194/jpmb.v3i1.66
Santoso, A. A., & Sukamulja, S. (2020). Penggunaan Kombinasi Indikator Sma, Ema, Macd, Rsi, Dan Mfi Untuk Menentukan Keputusan Beli Dan Jual Pada Saham-Saham Di Sektor Lq45 Bei Tahun 2018. Modus, 32(2), 159–174. https://doi.org/10.24002/modus.v32i2.3519
Simbolon, T. G. (2024). Data Jumlah Investor Pasar Modal di Indonesia hingga Februari 2024. DataIndonesia.Id.
Smith, D. M., Fauger̀e, C., & Wang, Y. (2013). Head head and shoulders above the rest the performance of institutional portfolio managers who use technical analysis. Research in Finance, 29, 167–189. https://doi.org/10.1108/S0196-3821(2013)0000029010
Suryanto, S. (2021). Analisis Teknikal Dengan Menggunakan Moving Average Convergence-Divergence Dan Relative Strength Index Pada Saham Perbankan. Jurnal Ilmu Keuangan Dan Perbankan (JIKA), 11(1), 51–65. https://doi.org/10.34010/jika.v11i1.5896
Tika Denisa Simanjuntak, Isfenti Sadalia, & Nisrul Irawati. (2023). Technical Analysis As the Basis for Decision Making in Stock Investment in Pt. Bank Mestika Dharma.Tbk in the Indonesian Capital Market (During the Covid Pandemic January 2020 - June 2021). International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS), 3(5), 1474–1490. https://doi.org/10.54443/ijebas.v3i5.1085
Tiovandi, M. R. (2024). Anailisis Dengan Indikator Bollinger Band dan Stochastic Oscillator Pada Saham Serta Fundamental Perusahaan LQ 45 Sub Sektor Perbankan. 1(6), 249–257.
Wang, J., & Kim, J. (2018). Predicting stock price trend using MACD optimized by historical volatility. Mathematical Problems in Engineering, 2018. https://doi.org/10.1155/2018/9280590
Published
2025-01-06
How to Cite
ARTA, Sri Nurpiana; HAANURAT, Andi Ifayani; JAYA, Asri.
Comparison of MACD and Stochastic in Optimizing Stock Investment Strategy.
E-Jurnal Akuntansi, [S.l.], v. 35, n. 4, jan. 2025.
ISSN 2302-8556.
Available at: <https://ojs.unud.ac.id/index.php/akuntansi/article/view/122490>. Date accessed: 30 apr. 2025.
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