Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analysis of Nifty 50 index stock market trends using hybrid machine learning model in quantum finance Subject The topic of the resource National stock exchange fifty; Principle component analysis; Stock market; Technical indicators; Time series forecast Description An account of the resource Predicting equities market trends is one of the most challenging tasks for market participants. This study aims to apply machine learning algorithms to aid in accurate Nifty 50 index trend predictions. The paper compares and contrasts four forecasting methods: artificial neural networks (ANN), support vector machines (SVM), naive bayes (NB), and random forest (RF). In this study, the eight technical indicators are used, and then the deterministic trend layer is used to translate the indications into trend signals. The principal component analysis (PCA) method is then applied to this deterministic trend signal. This study's main influence is using the PCA technique to find the essential components from multiple technical indicators affecting stock prices to reduce data dimensionality and improve model performance. As a result, a PCA-machine learning (ML) hybrid forecasting model was proposed. The experimental findings suggest that the technical factors are signified as trend signals and that the PCA approach combined with ML models outperforms the comparative models in prediction performance. Utilizing the first three principal components (percentage of explained variance=80%), experiments on the Nifty 50 index show that support vector classifier (SVC) with radial basis function (RBF) kernel achieves good accuracy of (0.9968) and F1-score (0.9969), and the RF model achieves an accuracy of (0.9969) and F1-Score (0.9968). In area under the curve (AUC) performance, SVC (RBF and Linear kernels) and RF have AUC scores of 1. 2023 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Manjunath C.; Marimuthu B.; Ghosh B. Source A related resource from which the described resource is derived International Journal of Electrical and Computer Engineering, Vol-13, No. 3, pp. 3549-3560. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijece.v13i3.pp3549-3560" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijece.v13i3.pp3549-3560</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149106688&amp;doi=10.11591%2Fijece.v13i3.pp3549-3560&amp;partnerID=40&amp;md5=cf8a5be4173b9508721b5ea5f7f6664f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149106688&amp;doi=10.11591%2fijece.v13i3.pp3549-3560&amp;partnerID=40&amp;md5=cf8a5be4173b9508721b5ea5f7f6664f</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 20888708 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Manjunath C., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, India; Marimuthu B., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Bengaluru, India; Ghosh B., Symbiosis Institute of Business Management, Symbiosis International (Deemed University), Bengaluru, India