Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item The Causal Effect of Financial News on Indian Stock Market(Institute of Electrical and Electronics Engineers Inc., 2022) Varghese, R.R.; Mohan, B.R.The impact of the news media on stock prices has increasingly risen to the forefront of discussion as a result of in-depth stock market research. The aim of this paper is to investigate the presence of causal links between financial news and stock market values. Granger causality between the stock market and sentiment of financial news is investigated by bivariate analysis. Then the sliding window approach quantifies the causal relationship between news sentiment and stock price. We find a positive correlation between the sentiment of financial news and in the variation of the stock price and the effect of the news is at its peak on the same day as the news is released. Our findings lend quantitative support to the idea that movements in financial markets and movements in financial news are inextricably linked. © 2022 IEEE.Item Dynamics of Nonlinear Causality: Exploring the Influence of Positive and Negative Financial News on the Indian Equity Market(Institute of Electrical and Electronics Engineers Inc., 2023) Varghese, R.R.; Mohan, B.R.Recent attention has focused on the interplay between news media and stock prices, prompted by extensive exploration of stock market dynamics. This study is designed to examine the existence of non-linear causal links between positive and negative financial news and stock market valuations. Employing sentiment analysis, the Finbert model evaluates news content, while the Transfer Entropy method assesses the impact of both positive financial news and negative news. Investigating the causal relationships between fluctuations in positive and negative news and stock price performance across diverse companies through transfer entropy analysis, our findings confirm the evident disparity in the influence of positive and negative news on daily stock prices. Quantification of these effects adopts the Sliding Window approach. Furthermore, our evaluations indicate that negative financial news exerts a more significant influence on stock prices compared to positive financial news. These outcomes bolster the concept of an asymmetric effect, wherein negative sentiment wields a more substantial influence compared to its positive counterpart. © 2023 IEEE.Item Time based Sentiment Analysis of Financial Headlines using Recurrent Neural Network(Institute of Electrical and Electronics Engineers Inc., 2025) Shashank, G.; Pandey, G.; Koolagudi, S.G.The sentiment of financial news headlines plays an important role in understanding market trends and investor behavior. This study proposes a Recurrent Neural Network (RNN)-based model for accurately classifying the sentiment of financial headlines into positive, neutral, and negative categories. Keeping in mind the time trend based behavior of the financial world, and the impact of certain keywords relevant only in the financial context, the RNN architecture captures the contextual nuances often overlooked by traditional methods. To address the domain-specific challenges of financial language and the inherent trends based on the time series based data, the model aims to incorporate embeddings that are fine-tuned on financial text along with a capacity to capture time based context. Experiments conducted on a dataset of financial stocks for a period from 2003 to 2020 help demonstrate the effectiveness of the proposed RNN compared to other benchmark methods. It provides a result with 97% accuracy and accurately captures the context of verbal and time based sentiment context. © 2025 IEEE.