{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T07:16:16Z","timestamp":1776410176635,"version":"3.51.2"},"reference-count":76,"publisher":"Emerald","issue":"5","license":[{"start":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T00:00:00Z","timestamp":1679356800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["DTA"],"published-print":{"date-parts":[[2023,11,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The stock market generates massive databases of various financial companies that are highly volatile and complex. To forecast daily stock values of these companies, investors frequently use technical analysis or fundamental analysis. Data mining techniques coupled with fundamental and technical analysis types have the potential to give satisfactory results for stock market prediction. In the current paper, an effort is made to investigate the accuracy of stock market predictions by using the combined approach of variables from technical and fundamental analysis for the creation of a data mining predictive model.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>We chose 381 companies from the National Stock Exchange of India's CNX 500 index and conducted a two-stage data analysis. The first stage is identifying key fundamental variables and constructing a portfolio based on that study. Artificial neural network (ANN), support vector machines (SVM) and decision tree J48 were used to build the models. The second stage entails applying technical analysis to forecast price movements in the companies included in the portfolios. ANN and SVM techniques were used to create predictive models for all companies in the portfolios. We also estimated returns using trading decisions based on the model's output and then compared them to buy-and-hold returns and the return of the NIFTY 50 index, which served as a benchmark.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results show that the returns of both the portfolios are higher than the benchmark buy-and-hold strategy return. It can be concluded that data mining techniques give better results, irrespective of the type of stock, and have the ability to make up for poor stocks. The comparison of returns of portfolios with the return of NIFTY as a benchmark also indicates that both the portfolios are generating higher returns as compared to the return generated by NIFTY.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>As stock prices are influenced by both technical and fundamental indicators, the current paper explored the combined effect of technical analysis and fundamental analysis variables for Indian stock market prediction. Further, the results obtained by individual analysis have also been compared. The proposed method under study can also be utilized to determine whether to hold stocks for the long or short term using trend-based research.<\/jats:p><\/jats:sec>","DOI":"10.1108\/dta-04-2022-0142","type":"journal-article","created":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T02:03:26Z","timestamp":1679364206000},"page":"780-800","source":"Crossref","is-referenced-by-count":11,"title":["Data mining\u2013based stock price prediction using hybridization of technical and fundamental 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(2007), \u201cForecasting the jordanian stock prices using artificial neural network\u201d, Intelligent Engineering Systems Through Artificial Neural Networks, ASME Press, NY, USA."},{"key":"key2023111509330399600_ref076","year":"2012","journal-title":"Data Mining Concepts and Techniques"},{"issue":"2","key":"key2023111509330399600_ref031","first-page":"136","article-title":"Prediction of stock performance using analytical techniques","volume":"5","year":"2013","journal-title":"Journal of Emerging Technologies in Web Intelligence"},{"key":"key2023111509330399600_ref032","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.jfineco.2005.09.010","article-title":"Do industries lead the stock market?","volume":"83","year":"2007","journal-title":"Journal of Financial Economics"},{"issue":"4","key":"key2023111509330399600_ref033","first-page":"145","article-title":"The use of data mining techniques and support vector regression for financial forecasting","volume":"6","year":"2013","journal-title":"International Journal of Database Theory and Application"},{"key":"key2023111509330399600_ref034","doi-asserted-by":"crossref","first-page":"2510","DOI":"10.1016\/j.asoc.2010.09.007","article-title":"Forecasting stock markets using wavelet transforms and recurrent neural networks: an integrated system based on artificial bee colony algorithm","volume":"11","year":"2011","journal-title":"Applied Soft Computing"},{"key":"key2023111509330399600_ref035","doi-asserted-by":"crossref","first-page":"2870","DOI":"10.1016\/j.eswa.2007.05.035","article-title":"Application of wrapper approach and composite classifier to the stock trend prediction","volume":"34","year":"2008","journal-title":"Expert Systems with Applications"},{"key":"key2023111509330399600_ref036","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/S0167-9236(03)00086-1","article-title":"Credit rating analysis with support vector machines and neural networks: a market comparative study","volume":"37","year":"2004","journal-title":"Decision Support Systems"},{"key":"key2023111509330399600_ref037","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/0167-2231(87)90007-8","article-title":"An empirical investigation of the long run behavior of real exchange rates","volume":"27","year":"1987","journal-title":"Carnegie Rochester Conference Series on Public Policy"},{"key":"key2023111509330399600_ref038","doi-asserted-by":"crossref","first-page":"5311","DOI":"10.1016\/j.eswa.2010.10.027","article-title":"Predicting direction of stock price index movement using artificial neural networks and support vector machines: the sample of the Istanbul stock exchange","volume":"38","year":"2011","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"key2023111509330399600_ref039","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1002\/isaf.1518","article-title":"Application and performance of data mining techniques in stock market: a review","volume":"29","year":"2022","journal-title":"Intelligent Systems in Accounting, Finance and Management"},{"key":"key2023111509330399600_ref040","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0925-2312(03)00372-2","article-title":"Financial time series forecasting using support vector machines","volume":"55","year":"2003","journal-title":"Neurocomputing"},{"key":"key2023111509330399600_ref041","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.eswa.2005.10.007","article-title":"Artificial neural networks with evolutionary instance selection for financial forecasting","volume":"30","year":"2006","journal-title":"Expert Systems with Applications"},{"key":"key2023111509330399600_ref042","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/S0957-4174(00)00027-0","article-title":"Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index","volume":"19","year":"2000","journal-title":"Expert Systems with Applications"},{"key":"key2023111509330399600_ref043","first-page":"1","article-title":"Stock market prediction system with modular neural network","year":"1990"},{"key":"key2023111509330399600_ref044","doi-asserted-by":"crossref","unstructured":"Kohli, P.P.S., Zargar, S., Arora, S. and Gupta, P. (2019), \u201cStock prediction using machine learning algorithms\u201d, Applications of Artificial Intelligence Techniques in Engineering, Advances in Intelligent Systems and Computing book series, Springer, Vol. 698, pp. 405-414.","DOI":"10.1007\/978-981-13-1819-1_38"},{"key":"key2023111509330399600_ref045","article-title":"Forecasting stock index movement: a comparison of support vector machines and random forest","volume-title":"Indian Institute of Capital Markets 9th Capital Markets Conference Paper","year":"2006"},{"key":"key2023111509330399600_ref046","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1109\/TNN.2007.891629","article-title":"A hybrid neurogenetic approach for stock forecasting","volume":"18","year":"2007","journal-title":"IEEE Transactions on Neural Networks"},{"key":"key2023111509330399600_ref047","first-page":"1","article-title":"Neural networks and investors sentiment measures for stock market trend prediction","volume":"27","year":"2011","journal-title":"Journal of Theoretical Applied Information Technology"},{"key":"key2023111509330399600_ref048","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0169-2070(99)00048-5","article-title":"Forecasting stock indices: a comparison of classification and level estimation models","volume":"16","year":"2000","journal-title":"International Journal of Forecasting"},{"key":"key2023111509330399600_ref049","unstructured":"Majumder, M. and Hussian, M.D. (2007), \u201cForecasting of Indian stock market index using artificial neural network\u201d, Information Science, pp. 98-105."},{"issue":"1\/2","key":"key2023111509330399600_ref050","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1504\/IJDSRM.2017.084002","article-title":"Forecasting of future stock prices using neural networks and genetic algorithms","volume":"7","year":"2017","journal-title":"International Journal of Decision Sciences, Risk and Management"},{"key":"key2023111509330399600_ref051","unstructured":"Mittal, A. and Goel, A. 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