Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies

Rosillo, R.; de la Fuente, D.; Brugos, J. A. L.

doi:10.1080/00036846.2011.631894

Cited by 105Stock Market Forecasting MethodsFinancial Markets and Investment StrategiesFinancial Analysis and Corporate Governance

The DOI matches its Crossref record; 26 of the 28 references it cites were found in a registry or an index.

Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies

Open access

Rosillo, R., de la Fuente, D., Brugos, J. A. L.·2013·Applied Economics

DOI 10.1080/00036846.2011.631894

Open this paper in CoChat — free account

Abstract

The aim of this research is to examine the result of the application of the indicators Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Momentum and Stochastic in different companies of the Spanish continuous market. By using these indicators, it is intended to give purchase and sale recommendations to small investors. The generation of great capital gains depends on the type of the stock exchange company and the indicator which is being used. In addition, this research solves the problems in case of ambiguity, in the indicators, for the traders.

Integrity signals

Registry

Crossref · 10.1080/00036846.2011.631894

Cites

26 of 26 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The two rules are still widely used as trading indicators in the market.
“As of today, the two rules are still widely used as trading indicators in the market [16,17].”
From Revisiting the Performance of MACD and RSI Oscillators (2014) · cites this paper as [17]

EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*
Malkiel, B. G., & Fama, E. F. (1970) · The Journal of Finance · doi:10.1111/j.1540-6261.1970.tb00518.x · Cited by 24,478
Efficient capital markets: A review of theory and empirical work
Fama, E. F. (1970) · The Journal of Finance · doi:10.2307/2325486 · Cited by 13,635
The Behavior of Stock-Market Prices
Fama, E. F. (1965) · The Journal of Business · doi:10.1086/294743 · Cited by 8,803
Simple technical trading rules and the stochastic properties of stock returns
BROCK, W., LAKONISHOK, J., & LeBARON, B. (1992) · The Journal of Finance · doi:10.1111/j.1540-6261.1992.tb04681.x · Cited by 2,301
The use of technical analysis in the foreign exchange market
Taylor, M., & Allen, H. (1992) · Journal of International Money and Finance · doi:10.1016/0261-5606(92)90048-3 · Cited by 1,071
The new Palgrave dictionary of money and finance
Middleton, R. (1992) · Cited by 630
New Concepts in Technical Trading Systems
Wilder, J. (1978) · Cited by 461
Simple Technical Trading Rules and the Stochastic Properties of Stock Returns
Brock, W., Lakonishok, J., & LeBaron, B. D. (1992) · The Journal of Finance · doi:10.2307/2328994 · Cited by 441
The obstinate passion of Foreign Exchange Professionals: \ntechnical analysis
Menkhoff, L., & Taylor, M. (2006) · Warwick Research Archive Portal (University of Warwick) · Cited by 437
Charts, Noise and Fundamentals in the London Foreign Exchange Market
Allen, H., & Taylor, M. (1990) · The Economic Journal · doi:10.2307/2234183 · Cited by 384
Technical Analysis in Financial MarketsPreprint
Griffioen, G. A. W. (2004) · SSRN Electronic Journal · doi:10.2139/ssrn.566882 · Cited by 376
Do Momentum-Based Strategies Still Work in Foreign Currency Markets?
Okunev, J., & White, D. R. (2003) · Journal of Financial and Quantitative Analysis · doi:10.2307/4126758 · Cited by 310
A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices—1935 to 1994
Hudson, R., Dempsey, M., & Keasey, K. (1996) · Journal of Banking & Finance · doi:10.1016/0378-4266(95)00043-7 · Cited by 297
Naïve trading rules in financial markets and Wiener-Kolmogorov prediction theory: A study of “technical analysis”
Neftci, S. N. (1991) · The Journal of Business · doi:10.1086/296551 · Cited by 271
Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis
Osler, C. L. (2003) · The Journal of Finance · doi:10.1111/1540-6261.00588 · Cited by 231
Technical analysis and the London stock exchange: Testing the MACD and RSI rules using the FT30
Chong, T. T.-L., & Ng, W.-K. (2008) · Applied Economics Letters · doi:10.1080/13504850600993598 · Cited by 220
In defense of technical analysis
TREYNOR, J. L., & FERGUSON, R. (1985) · The Journal of Finance · doi:10.1111/j.1540-6261.1985.tb05000.x · Cited by 152
Intraday technical trading in the foreign exchange market
Neely, C. J., & Weller, P. A. (2003) · Journal of International Money and Finance · doi:10.1016/s0261-5606(02)00101-8 · Cited by 148
Technical trading strategies and return predictability: NYSE
Kwon, K.-Y., & Kish, R. J. (2002) · Applied Financial Economics · doi:10.1080/09603100010016139 · Cited by 128
Stop-loss orders and price cascades in currency markets
Osler, C. L. (2005) · Journal of International Money and Finance · doi:10.1016/j.jimonfin.2004.12.002 · Cited by 125
Do Momentum Based Strategies Still Work in Foreign Currency Markets?Preprint
White, D. R., & Okunev, J. (2001) · SSRN Electronic Journal · doi:10.2139/ssrn.264574 · Cited by 81
Psychological Barriers in the Foreign Exchange MarketPreprint
GRAUWE, P. D., & Decupere, D. (1992) · RePEc: Research Papers in Economics · Cited by 54
In Defense of Technical Analysis
Treynor, J. L., & Ferguson, R. (1985) · The Journal of Finance · doi:10.2307/2327800 · Cited by 48
Drivers of technical trend-following rules' profitability in world stock markets
Ülkü, N., & Prodan, E. (2013) · International Review of Financial Analysis · doi:10.1016/j.irfa.2013.08.005 · Cited by 36
Currency Strategy: The Practitioner's Guide to Currency Investing, Hedging and Forecasting
Henderson, C. (2002) · Medical Entomology and Zoology · Cited by 30
Untitled work
Mills (1997) · doi:10.1002/(sici)1099-1158(199710)2:4

Flagged first, then by citations

2 of the 28 references couldn’t be matched to a known paper.

Research works printed but not linked: 4

De Grauwe P, 1992, Journal of International and Comparative Economics, 1, 87
10.1257/jel.45.4.936 · DOI · Paper page
10.1002/(SICI)1099-1158(199710)2:4<319::AID-JFE53>3.0.CO;2-6 · DOI
Osler CL, 2000, Federal Reverse Bank of New York Economic Policy Review, 6, 53

Sorted by citations

Revisiting the Performance of MACD and RSI Oscillators
Chong, T., Ng, W.-K., & Liew, V. (2014) · Journal of Risk and Financial Management · doi:10.3390/jrfm7010001 · Cited by 95
“As of today, the two rules are still widely used as trading indicators in the market [16,17].”
Background
Deep-learning-based stock market prediction incorporating ESG sentiment and technical indicators
Lee, H., Kim, J. H., & Jung, H. S. (2024) · Scientific Reports · doi:10.1038/s41598-024-61106-2 · Cited by 86
Testing the efficient market hypothesis in Latin American stock markets
Sánchez-Granero, M. Á., Ponguillo, K. A. B., Ramos-Requena, J. P., & Segovia, J. E. T. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.123082 · Cited by 56
Assessing the usefulness of online message board mining in automatic stock prediction systems
Gálvez, R. H., & Gravano, A. (2017) · Journal of Computational Science · doi:10.1016/j.jocs.2017.01.001 · Cited by 45
A novel hybrid model based on recurrent neural networks for stock market timing
Qiu, Y., Yang, H., Lu, S., & Chen, W. (2020) · Soft Computing · doi:10.1007/s00500-020-04862-3 · Cited by 41
An adaptive robust portfolio optimization model with loss constraints based on data-driven polyhedral uncertainty sets
Fernandes, B., Street, A., Valladão, D., & Fernandes, C. A. C. (2016) · European Journal of Operational Research · doi:10.1016/j.ejor.2016.05.038 · Cited by 37
Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach
Wang, L., An, H., Liu, X., & Huang, X. (2015) · Applied Energy · doi:10.1016/j.apenergy.2015.08.132 · Cited by 37
Drivers of technical trend-following rules' profitability in world stock markets
Ülkü, N., & Prodan, E. (2013) · International Review of Financial Analysis · doi:10.1016/j.irfa.2013.08.005 · Cited by 36
Machine learning applied in the stock market through the Moving Average Convergence Divergence (MACD) indicator
Aguirre, A. A. A., Medina, R. A. R., & Méndez, N. D. D. (2020) · Investment Management and Financial Innovations · doi:10.21511/imfi.17(4).2020.05 · Cited by 36
Stock Market Simulation Using Support Vector Machines
Rosillo, R., Giner, J., & de la Fuente, D. (2014) · Journal of Forecasting · doi:10.1002/for.2302 · Cited by 32
Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market
Kang, B.-K. (2021) · Journal of risk and financial management · doi:10.3390/jrfm14010037 · Cited by 29
Technical analysis of three stock oscillators testing MACD, RSI and KDJ rules in SH & SZ stock markets
Wu, M., & Diao, X. (2015) · International Conference on Computer Science and Network Technology (ICCSNT) · doi:10.1109/iccsnt.2015.7490760 · Cited by 26
Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators
Jung, H. S., Lee, S. H., Lee, H., & Kim, J. H. (2023) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.034466 · Cited by 25
Technical Analysis, Fundamental Analysis, and Ichimoku Dynamics: A Bibliometric Analysis
Almeida, L., & Vieira, E. F. S. (2023) · Risks · doi:10.3390/risks11080142 · Cited by 24
Forecasting IBEX-35 moves using support vector machines
Dunis, C. L., Rosillo, R., de la Fuente, D., & Díez, R. P. (2012) · Neural Computing and Applications · doi:10.1007/s00521-012-0821-9 · Cited by 24
An Algorithm for Testing the Efficient Market Hypothesis
Boboc, I.-A., & Dinică, M.-C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0078177 · Cited by 23
Importance of Event Binary Features in Stock Price Prediction
Song, Y., & Lee, J. (2020) · Applied Sciences · doi:10.3390/app10051597 · Cited by 23
Cryptocurrency direction forecasting using deep learning algorithms
Cherati, M. R., Haeri, A., & Ghannadpour, S. F. (2021) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2021.1899179 · Cited by 22
Stock Price Movement Prediction Based on a Deep Factorization Machine and the Attention Mechanism
Zhang, X., Liu, S., & Zheng, X. (2021) · Mathematics · doi:10.3390/math9080800 · Cited by 20
Moving Average Convergence-Divergence (MACD) Trading Rule: An Application in Nepalese Stock Market "NEPSE"
Vaidya, R. (2020) · Quantitative Economics and Management Studies · doi:10.35877/454ri.qems197 · Cited by 18
Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator
Aguirre, A. A. A., Méndez, N. D. D., & Medina, R. A. R. (2021) · Journal of Economics Finance and Administrative Science · doi:10.1108/jefas-06-2020-0203 · Cited by 16
Can investors profit by utilizing technical trading strategies? Evidence from the Korean and Chinese stock markets
Ni, Y., Day, M.-Y., Cheng, Y., & Huang, P. (2022) · Financial Innovation · doi:10.1186/s40854-022-00358-1 · Cited by 16
Market turning points forecasting using wavelet analysis
Bai, L., Yan, S., Zheng, X., & Chen, B. M. (2015) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2015.05.027 · Cited by 16
Decoding Bitcoin: leveraging macro- and micro-factors in time series analysis for price prediction
Jung, H. S., Kim, J. H., & Lee, H. (2024) · PeerJ Computer Science · doi:10.7717/peerj-cs.2314 · Cited by 16
The effectiveness of the combined use of VIX and Support Vector Machines on the prediction of S&P 500
Rosillo, R., Giner, J., & de la Fuente, D. (2013) · Neural Computing and Applications · doi:10.1007/s00521-013-1487-7 · Cited by 14
Picking Buy-Sell Signals: A Practitioner’s Perspective on Key Technical Indicators for Selected Indian Firms
Shalini, T. R., Pranav, S., & Utkarsh, S. (2019) · Studies in Business and Economics · doi:10.2478/sbe-2019-0054 · Cited by 13
Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns
Day, M.-Y., Ni, Y., & Huang, P. (2019) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.03.038 · Cited by 12
Asymptotic Meta Learning for Cross Validation of Models for Financial Data
Xiang, H., Lin, J., Chen, C., & Kong, Y. (2020) · IEEE Intelligent Systems · doi:10.1109/mis.2020.2973255 · Cited by 12
Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency
Ponguillo, K. A. B., Ramos-Requena, J. P., Segovia, J. E. T., & Sánchez-Granero, M. Á. (2021) · Mathematics · doi:10.3390/math9020179 · Cited by 12
A hybrid method based on neural networks and a meta-heuristic bat algorithm for stock price prediction
Golmaryami, M., Behzadi, M., & Ahmadzadeh, M. (2015) · International Conference on Knowledge-Based Engineering and Innovation · doi:10.1109/kbei.2015.7436059 · Cited by 11
Impact of self-learning based high-frequency traders on the stock market
Mansurov, K., Semenov, A., Grigoriev, D., Radionov, A., & Ibragimov, R. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120567 · Cited by 10
Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?
Strobel, M., & Auer, B. R. (2017) · International Review of Economics & Finance · doi:10.1016/j.iref.2017.10.012 · Cited by 10
Evaluating the Prediction Accuracy of MACD and RSI for Different Stocks in Terms of Standard Market Suggestions
Sami, H., Ayman, K., Ahshan, et al. (2022) · Canadian Journal of Business and Information Studies · doi:10.34104/cjbis.022.01370143 · Cited by 10
Profitability Edge by Dynamic Back Testing Optimal Period Selection for Technical Parameters Optimization, in Trading Systems with Forecasting
Vezeris, D., Schinas, C. J., & Papaschinopoulos, G. (2016) · Computational Economics · doi:10.1007/s10614-016-9640-x · Cited by 10
A framework for identifying the onset of landslide acceleration based on the exponential moving average (EMA)
Wang, J., Ju, N., Tie, Y., Bai, Y., & Ge, H. (2023) · Journal of Mountain Science · doi:10.1007/s11629-023-7905-0 · Cited by 9
Fluctuation-driven price dynamics and investment strategies
Li, Y., Zheng, B., Chen, T., & Jiang, X.-F. (2017) · PLoS ONE · doi:10.1371/journal.pone.0189274 · Cited by 9
Stock Trend Prediction using SV-kNNC and SOM
Sinaga, F. M., Jonas, M., Felix, & Halim, A. (2019) · International Conference on Informatics and Computing (ICIC) · doi:10.1109/icic47613.2019.8985731 · Cited by 10
Improving Real Estate Investment Trusts (REITs) time-series prediction accuracy using machine learning and technical analysis indicators
Habbab, F. Z., Kampouridis, M., & Papastylianou, T. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-024-11037-1 · Cited by 10
Optimal lengths of moving averages for the MACD oscillator for companies listed on the Warsaw Stock Exchange
Borowski, K., & Pruchnicka-Grabias, I. (2019) · Bank i Kredyt · doi:10.5604/01.3001.0054.5821 · Cited by 8
Testing the Efficient Market Hypothesis and the Model-Data Paradox of Chaos on Top Currencies from the Foreign Exchange Market (FOREX)
Sandubete, J. E., Beleña, L., & Villalobos, J. C. G. (2023) · Mathematics · doi:10.3390/math11020286 · Cited by 10
Performance of generated moving average strategies in natural gas futures prices at different time scales
Liu, X., An, H., & Wang, L. (2015) · Journal of Natural Gas Science and Engineering · doi:10.1016/j.jngse.2015.03.031 · Cited by 8
The Performance of Exponential Moving Average, Moving Average Convergence-Divergence, Relative Strength Index and Momentum Trading Rules in the Pakistan Stock Market
Khand, S., Anand, V., Qureshi, M. N., & Katper, N. K. (2019) · Indian Journal of Science and Technology · doi:10.17485/ijst/2019/v12i26/145117 · Cited by 7
An empirical study of factors affecting investors’ decisions in the Iranian Stock Market: A combined DEMATEL-ANP approach
Sardasht, M. S., Moradi, M., & Rahmani, H. (2014) · Aestimatio The IEB International Journal of Finance · doi:10.5605/ieb.9.6 · Cited by 7
Optimal and Non-Optimal MACD Parameter Values and Their Ranges for Stock-Index Futures: A Comparative Study of Nikkei, Dow Jones, and Nasdaq
Kang, B.-K. (2023) · Journal of risk and financial management · doi:10.3390/jrfm16120508 · Cited by 6
Stock Price Movement Classification Using Ensembled Model of Long Short-Term Memory (LSTM) and Random Forest (RF)
Gunawan, A. E. K., & Wibowo, A. (2023) · JOIV International Journal on Informatics Visualization · doi:10.30630/joiv.7.4.01640 · Cited by 6
Is Technical Analysis Profitable on Renewable Energy Stocks? Evidence from Trend-Reinforcing, Mean-Reverting and Hybrid Fractal Trading Systems
Nor, S. M., Zawawi, N. H. M., Wickremasinghe, G. B., & Halim, Z. A. (2023) · Axioms · doi:10.3390/axioms12020127 · Cited by 6
Cryptocurrency Exchange Simulation
Mansurov, K., Semenov, A., Grigoriev, D., Radionov, A., & Ibragimov, R. (2024) · Computational Economics · doi:10.1007/s10614-023-10495-z · Cited by 6
Mechanisms of Stock Selection and Its Capital Weighing in the Portfolio Design Based on the MACD-K-Means-Mean-VaR Model
Sukono, S., Rosadi, D., Maruddani, D. A. I., Ibrahim, R. A., & Johansyah, M. D. (2024) · Mathematics · doi:10.3390/math12020174 · Cited by 5
Using Momentum Analysis to Explain and Forecast the Outcome of International Negotiations
Bjola, C. (2015) · International Negotiation · doi:10.1163/15718069-12341309 · Cited by 5
A Dynamic Level Technical Indicator Model for Oil Price Forecasting
Oyemade, D. A., & Enebeli, D. (2021) · Global Journal of Computer Science and Technology · doi:10.34257/gjcstgvol21is1pg5 · Cited by 5
Design of stock price prediction model with various configuration of input features
Song, Y., & Lee, J. (2019) · International Conference on Artificial Intelligence, Information Processing and Cloud Computing (AIIPCC) · doi:10.1145/3371425.3371432 · Cited by 5
Sustainable investing: do ESG risks shift market dynamics?
Farhadi, N., & Hair, J. F. (2025) · Journal of Sustainable Finance & Investment · doi:10.1080/20430795.2025.2513250 · Cited by 4
The Relationship between VIX and Technical Indicator: The Analysis of Shared-Frailty Model
Chen, J.-H., Hussain, S., & Chen, F.-Y. (2023) · doi:10.47260/jafb/1335 · Cited by 4
Portfolios in the Ibex 35 before and after the Global Financial Crisis
Adame-García, V., Rodríguez, F. F., & Sosvilla‐Rivero, S. (2016) · Applied Economics · doi:10.1080/00036846.2016.1145352 · Cited by 4
Random Regression Forest Model using Technical Analysis Variables
Emir, Ş., Dınçer, H., Hacıoğlu, Ü., & Yuksel, S. (2016) · International Journal of Finance & Banking Studies (2147-4486) · doi:10.20525/ijfbs.v5i3.461 · Cited by 3
Finding Optimal Parameter Values for the MACD Indicator: Evidence From the Japanese Nikkei 225 Futures Market Using a New Methodology
Kang, B.-K. (2022) · International Journal of Financial Research · doi:10.5430/ijfr.v13n3p1 · Cited by 3
Improving REITs Time Series Prediction Using ML and Technical Analysis Indicators
Habbab, F. Z., Kampouridis, M., & Papastylianou, T. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191969 · Cited by 3
Teknik Analiz İndikatörlerinin Etkinlik Analizi: Borsa İstanbul Turizm Sektörü Üzerine Bir Uygulama
BİLEN, K., & Bahar, O. (2023) · Anatolia Turizm Araştırmaları Dergisi · doi:10.17123/atad.1291666 · Cited by 3
Automate the identification of technical patterns: a K-nearest-neighbour model approach
Li, D., Li, Z., & Li, R. (2017) · Applied Economics · doi:10.1080/00036846.2017.1383596 · Cited by 3
Moving Average Convergence / Devergerance and Relative Strength Index Applied to Predict Price of ASE
Alalaya, M., Hani, A., & Alawad, A. (2018) · International Journal of Business and Social Science · doi:10.30845/ijbss.v9n6a5 · Cited by 3
Trend Analysis Techniques in Forecasting Human Behaviour Evolution
Elbayoudi, A., Lotfi, A., Langensiepen, C. S., & Appiah, K. (2017) · International Conference on PErvasive Technologies Related to Assistive Environments (PETRA) · doi:10.1145/3056540.3076198 · Cited by 3
Affective Analytics and Visualization for Ensemble Event-Driven Stock Market Forecasting
Joshi, P., & Afli, H. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-68007-7_3 · Cited by 3
A Review of Stock Trend Prediction with Combination of Effective Multi Technical Indicator Strategy
Pheng, L. G., Tay, C. C., Foong, M., Yusof, N., & Singh, D. K. A. P. J. (2022) · International Journal of Managing Information Technology · doi:10.5121/ijmit.2022.14101 · Cited by 3
ANALISIS TEKNIKAL DENGAN MENGGUNAKAN MOVING AVERAGE CONVERGENCE-DIVERGENCE DAN RELATIVE STRENGTH INDEX PADA SAHAM PERBANKAN
Suryanto, S. (2021) · Jurnal Ilmu Keuangan dan Perbankan (JIKA) · doi:10.34010/jika.v11i1.5896 · Cited by 12
Stock Price Movement Classification Using Ensembled Model of Long Short-Term Memory (LSTM) and Random Forest (RF)
Gunawan, A. E. K., & Wibowo, A. (2023) · JOIV International Journal on Informatics Visualization · doi:10.62527/joiv.7.4.1640 · Cited by 2
Optimizing Genetic Algorithm With Momentum Strategy for Technical Trading Rules: Evidence From Futures Markets
Li, S., Liu, Q., Liu, Q., & Tse, Y. (2024) · Journal of Futures Markets · doi:10.1002/fut.22543 · Cited by 2
Dynamic Financial Time Series Modeling with Rapid Adaptation via Meta Learning
Noor, K., & Fatima, U. (2024) · International Multi-Topic Conference · doi:10.1109/inmic64792.2024.11004384 · Cited by 2
Investor sentiment and optimizing traditional quantitative investments
Chen, Z., Li, W., & Huang, J. D. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.104227 · Cited by 2
Research on Strategy of HS300 Index Based on Random Forest
Huang, X. (2020) · doi:10.1109/cds49703.2020.00038 · Cited by 2
Different Stock Market Models Using Support Vector Machines
Rosillo, R., Giner, J., Puente, J., & Ponte, B. (2013) · International Journal of Trade Economics and Finance · doi:10.7763/ijtef.2013.v4.307 · Cited by 2
Temporal optimisation of signals emitted automatically by securities exchange indicators
Rodrigo Martín-García. Universidad Nacional de Educación a Distancia (UNED). Facultad de Ciencias Económicas y Empresariales. Departamento de Economía de la Empresa y Contabilidad. Senda del Rey, 1., García, R. M., Pérez, E. V., Area Manager, G. S. –. E. C., Sanz, R. A., & Universidad Nacional de Educación a Distancia (UNED). Facultad de Ciencias Económicas y Empresariales. Departamento de Economía de la Empresa y Contabilidad. Senda del Rey, 1. (2020) · Cuadernos de Gestión · doi:10.5295/cdg.170851rm · Cited by 2
Have trend-following signals in commodity futures markets become less reliable in recent years?
Auer, B. R. (2021) · Financial markets and portfolio management · doi:10.1007/s11408-021-00385-5 · Cited by 2
DATT-NGRU: a novel deep learning model with data augmentation for daily stock indexes prediction
Cen, Y., Wang, M., Cen, G., Cai, Y., Zhao, C., & Cheng, Z. (2022) · Kybernetes · doi:10.1108/k-04-2022-0629 · Cited by 2
USING THE RELATIVE STRENGTH INDEX FOR ACTIVE INVESTMENTS IN THE FOREIGN EXCHANGE MARKET
Bartkus, Č. (2018) · Modern Management Review · doi:10.7862/rz.2018.mmr.39 · Cited by 2
Optimal and Non-Optimal Parameter Values and Their Ranges for the MACD Technical Indicator for the Nikkei, Dow Jones and NASDAQ Stock-Index FuturesPreprint
Kang, B.-K. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4658378 · Cited by 2
Evaluation of Alternative Weighting Techniques on the Swedish Stock Market
Finnerman, E., & Kirchmann, C. R. (2015) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 2
Functional Linear Model with Prior Information of Subjects’ Network
Zhang, X., Zhang, Q.-Z., & Fang, K.-N. (2024) · Journal of Computational And Graphical Statistics · doi:10.1080/10618600.2024.2319163 · Cited by 1
An automated quantitative investment model of stock selection and market timing based on industry information
Liu, M., Sun, W., Chen, J., & Ren, M. (2024) · Egyptian Informatics Journal · doi:10.1016/j.eij.2024.100471 · Cited by 1
Green Finance and Marketing: Portfolio Optimization Approaches for Environmentally Responsible ETFs
Bozkurt, M. A., Ok, Ş., & Çelik, S. (2025) · Computational Economics · doi:10.1007/s10614-025-11187-6 · Cited by 1
Optimal and Non-Optimal MACD Parameter Ranges with Stop-Loss and Take-Profit Rules: Evidence from the Gold Market
Kang, B.-K. (2026) · Journal of risk and financial management · doi:10.3390/jrfm19030192 · Cited by 1
Fuzzy Decision Mechanism for Stock Market Trading
Çapkan, Y., ŞENOL, E., & Ulu, C. (2021) · European Journal of Science and Technology · doi:10.31590/ejosat.951586 · Cited by 1
Internal and External Determinants of Bank Syariah Indonesia Capital Gain during the Pandemic
Qadri, R. A., & Murwaningsari, E. (2023) · Journal of Governance Risk Management Compliance and Sustainability · doi:10.31098/jgrcs.v3i2.1875 · Cited by 1
BİST Katılım 30 Endeksinde Yer Alan Hisse Senetlerinin Teknik Analiz ile İncelenmesi
GÜNEŞ, H., & Murat, K. A. Y. A. (2025) · Süleyman Demirel Üniversitesi Vizyoner Dergisi · doi:10.21076/vizyoner.1560195 · Cited by 1
Predictability of Foreign Exchange Rates with the AR(1) Model
Hadjixenophontos, A., & Christodoulou-Volos, C. N. (2017) · RePEc: Research Papers in Economics · Cited by 1
Assessment of the effectiveness of Polish social responsible company portfolios based on moving averages
Jamróz, P., & Piekunko‐Mantiuk, I. (2019) · Optimum Economic Studies · doi:10.15290/oes.2019.04.98.13 · Cited by 1
Does Technical Analysis Win?
Neves, M. E., Leite, J., & Neves, R. (2022) · Advances in finance, accounting, and economics book series · doi:10.4018/978-1-7998-8609-9.ch017 · Cited by 1
Trading a través del indicador RSI con la aplicación de Algoritmos Genéticos para la implementación en el sector empresarial de las inversiones
Aguirre, A. A. A., Medina, R. A. R., & Méndez, N. D. D. (2022) · Desarrollo Gerencial · doi:10.17081/dege.14.2.5755 · Cited by 1
Predicción del índice IBEX-35 aplicando Máquinas de Soporte Vectorial y Redes Neuronales.
Camblor, R. R., Dunis, C. L., de la Fuente, D., & Pino, R. P. (2012) · Dialnet (Universidad de la Rioja)
Parameterized Trade on the Futures Market on the WIG20
Piekunko‐Mantiuk, I. (2019) · Folia Oeconomica Stetinensia · doi:10.2478/foli-2019-0008
Understanding Unconscious Bias by Large-scale Data Analysis
Tang, S. (2019) · eScholarship (California Digital Library)
Deep Learning for Financial Time-Series Data Analytics: An Image Processing Based Approach
Pongsena, W., Ditsayabut, P., Kerdprasop, N., & Kerdprasop, K. (2020) · International Journal of Machine Learning and Computing · doi:10.18178/ijmlc.2020.10.1.897
ANALISIS ENTRY DAN EXIT MENGGUNAKAN SIMPLE MOVING AVERAGE DAN STOCHASTIC OSCILLATOR PADA EMITEN UNVR
Ajisaputra, A. (2019) · Jurnal Manajemen · doi:10.26460/jm.v9i2.974
Análisis de la efectividad y estabilidad de una combinación de indicadores de Análisis Técnico (Estocástico y el Índice de Fuerza Relativa) en el mercado accionario colombiano en el Período 2009 – 2019
Oses, R., & Sebastián, J. (2020)
FOREX Movement Direction Predictions with Similar Wavelet Patterns
Raimundo, M. S. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-16-1781-2_41
Determining the Most Efficient Technical Indicator of Investing in Financial Markets Based on Trends, Volume, Momentum and Volatility
Lakhwan, D., & Dave, A. (2020) · Myśl Ekonomiczna i Polityczna · doi:10.26399/meip.3(70).2020.17/d.lakhwan/a.dave
What Do We Learn from Daily Leaders and Laggards in Stock Investment? Do They Help Outperform the Market Average?
Kim, D.-K., & Kim, S. (2022) · International Journal of Economics and Finance · doi:10.5539/ijef.v14n2p44
Technical Indicators
Tsinaslanidis, P. E., & Zapranis, A. D. (2015) · Springer eBooks · doi:10.1007/978-3-319-23636-0_7
On the Effectiveness of Technical Indicators in Digital Assets
Glas, T. N. (2022) · Advanced studies in diginomics and digitalization · doi:10.1007/978-3-030-95695-0_7
A comparative analysis of using Moving Average Convergence Divergence indicator in the forex market with risk-free investment strategies
Sejwar, K., & Sethi, M. (2022) · Cardiometry · doi:10.18137/cardiometry.2022.24.692698
A Systematic Review of Technical Analysis-Based Forecasting Techniques: Global v/s Indian Perspectives
Krishna R. Kedia, T. D. (2024) · Journal of Informatics Education and Research · doi:10.52783/jier.v4i2.768

Estudio sobre algunos indicadores de análisis técnico en la bolsa española
Montero, J. M. S., Rojas, F. J. G., & Domínguez Serrano, M. Á. (2000) · Deposito de Investigacion Universidad de Sevilla (University of Seville)
La Hipótesis Débil Del Mercado Eficiente: Análisis Intradiario Del RSI En El Mercado Bursátil Español (The Weak Efficient Market Hypothesis: Intraday Analysis of The RSI in The Spanish Stock Market)Preprint
Ruíz, V., Castellanos, A. R., & Martínez, M. Á. P. (2008) · SSRN Electronic Journal
RSI and MACD indicators integrated: evidence from S&P 500 and Li-Ning as an example
Xiao, H. (2023) · BCP Business & Management · doi:10.54691/bcpbm.v38i.3695 · Cited by 3
Revisiting the Performance of MACD and RSI Oscillators
Chong, T., Ng, W.-K., & Liew, V. (2014) · Journal of Risk and Financial Management · doi:10.3390/jrfm7010001 · Cited by 95
A Comparative study between returns on RSI and Stochastic RSI using the Buy and Hold Strategy on Indian Equities
Mehta, A. H., & Anchan, V. (2026) · The Journal of Theoretical Accounting Research · doi:10.53555/jtar.v22i1.69

Authors: Rosillo, R., de la Fuente, D., & Brugos, J. A. L.
Affiliations: Universidad de Oviedo (ES)
Corresponding author: Rosillo, R.
ORCID: Rosillo, R.
Venue: Applied Economics
Publisher: Informa UK Limited
Published: 2013-04
Volume: 45
Issue: 12
Pages: 1541-1550
ISSN: 0003-6846 (ISSN-L)
1466-4283
DOI: 10.1080/00036846.2011.631894
OpenAlex: W1986782333
Cited by: 105
References: 28
Citations by year: 2026: 5 · 2025: 5 · 2024: 10 · 2023: 14 · 2022: 10 · 2021: 11 · 2020: 10 · 2019: 11 · 2018: 2 · 2017: 6 · 2016: 4 · 2015: 8 · 2014: 3 · 2013: 4
FWCI: 7.21
Type: journal article
Language: en
Open access: green
hdl.handle.net
Licence: cc-by-nc-nd
Locations: Applied Economics (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educación, Cultura y Deporte) (submittedVersion, cc-by-nc-nd)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
Keywords: technical analysis, relative strength index, MACD, momentum indicators, stochastic oscillator, buy and sell recommendations, retail investors, Spanish stock market, stock price prediction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks