Deploying NLP Techniques for Earnings Call Transcripts for Financial Analysis: A Reverse Phenomenon Paradigm
subject: 'Inverse Effect'; Behavioral Finance; Earnings Call Transcripts; Earnings per Share; Efficient Market Hypothesis; Lexicon Based Sentiments Analysis; Market Performance; Polarity; Stock Price; Weak Market Hypothesis
description: This study analyses the influence of quarterly board room discussions conducted in the form of "Earnings Call Transcripts"and company's stock price changes in the subsequent periods. In this study, sentiments were extracted from the "textual quarterly transcripts"of three major software companies for the last ten years. The extracted sentiments were statistically analyzed for patterns and types. The study led to the development of a new response variable called the 'Inverse Effect'. The 'Inverse Effect' simply refers to the discordance between the sentiment in the boardroom discussions available in the document form and changes in the stock price movements. If the sentiment for the current quarter is positive and the changes in the stock price movements is also positive in the subsequent quarter, it is considered as "concordance"and if the changes in the stock price movements is opposite to the sentiments it will be called as "discordance"which is the inverse effect. The study basically looks at the areas where the Weak Market Hypothesis (WMH) is not valid.The findings emerged from the study suggest a possible causality between the sentiments in the transcripts and the stock price changes. It was also found that sentiment polarity, three-quarter average stock price and the previous quarter stock price are the key determinants of the 'Inverse Effect'. Based on the findings from the study, appropriate machine learning models were developed and evaluated to predict the 'Inverse Effect' on the performance of individual stocks of a few select companies. 2023 IEEE.
creator: Nagendra B.V.; Simha J.B.; Abhi S.; Kumar Chandar S.
source: 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, pp. 368-375.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2023-01-01
rights: Restricted Access
relation: ISBN: 979-835034148-5
format: Online
language: English
type: Conference paper
coverage: Nagendra B.V., Christ (Deemed to Be University), Bengaluru, India; Simha J.B., Reva University, Reva Academy for Corporate Excellence, Bangalore, India; Abhi S., Reva University, Reva Academy for Corporate Excellence, Bangalore, India; Kumar Chandar S., Christ (Deemed to Be University), Bengaluru, India