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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Financial Lexicon based Sentiment Prediction for Earnings Call Transcripts for Market Intelligence Subject The topic of the resource Classification; Earnings Call Transcripts (ECT); Inverse Effect; Lexicon; Sentiments; Stock Price Description An account of the resource Sentiment based stock price direction detection has been an exciting study in the field of finance which is drawing a lot of attention from the investor community. Sentiments are used to detect the changes in the stock price movements for the subsequent periods. Investor community uses these sentiments derived from news, celebrity speech and events to plan trading and investment strategies. Several studies have been done in the past with sentiments, but use of Earnings Call Transcripts (ECT) has not been explored for market intelligence hitherto. Standard dictionary based lexicons like Vader, AFINN and NRC have not performed well in finance as they are domain agnostic. There is a need to develop a financial lexicon based on the ECT corpora, which may provide a better lift over the standard lexicons. This study has observed that Vader has performed poorly as opposed to the newly developed financial lexicon. Machine learning based generative lexicon engine using Bayesian approach, which is termed as FNB Lex was developed in this research study to overcome the limitations of standard domain agnostic lexicons. The lexicon development was performed on quarterly Earning Call Transcripts (ECT) of sixteen IT companies spanning over ten years. The study also investigates the detection of inverse effect in stock price movements based on the sentiments of the previous period. Machine Learning (ML) models like Naive Bayes, FNB Lex, SVM and biLSTM were developed and their discriminatory powers were assessed. NB Lex provided much better lift in detecting the inverse effect as opposed to other models. 2024 IEEE. Creator An entity primarily responsible for making the resource Nagendra B.V.; Kumar Chandar S.; Simha J.B.; John Bazil J.A. Source A related resource from which the described resource is derived Proceedings - 2024 5th International Conference on Image Processing and Capsule Networks, ICIPCN 2024, pp. 595-603. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICIPCN63822.2024.00103" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICIPCN63822.2024.00103</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204783457&amp;doi=10.1109%2FICIPCN63822.2024.00103&amp;partnerID=40&amp;md5=4a4d6e405690728209abb81feec7b6e7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204783457&amp;doi=10.1109%2fICIPCN63822.2024.00103&amp;partnerID=40&amp;md5=4a4d6e405690728209abb81feec7b6e7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036717-1 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nagendra B.V., Christ University, Bengaluru, India; Kumar Chandar S., Christ University, Bengaluru, India; Simha J.B., REVA University, REVA Academy for Corporate Excellence, India; John Bazil J.A., Christ University, Bengaluru, India