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The Hype Index: an NLP-driven Measure of Market News Attention
Zheng Cao, Wanchaloem Wunkaew, Helyette Geman
https://arxiv.org/abs/2506.06329 https://

The Hype Index: an NLP-driven Measure of Market News Attention
This paper introduces the Hype Index as a novel metric to quantify media attention toward large-cap equities, leveraging advances in Natural Language Processing (NLP) for extracting predictive signals from financial news. Using the S&P 100 as the focus universe, we first construct a News Count-Based Hype Index, which measures relative media exposure by computing the share of news articles referencing each stock or sector. We then extend it to the Capitalization Adjusted Hype Index, adjusts for …

Stock Market Telepathy: Graph Neural Networks Predicting the Secret Conversations between MINT and G7 Countries
Nurbanu Bursa
https://arxiv.org/abs/2506.01945

Stock Market Telepathy: Graph Neural Networks Predicting the Secret Conversations between MINT and G7 Countries
Emerging economies, particularly the MINT countries (Mexico, Indonesia, Nigeria, and Türkiye), are gaining influence in global stock markets, although they remain susceptible to the economic conditions of developed countries like the G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States). This interconnectedness and sensitivity of financial markets make understanding these relationships crucial for investors and policymakers to predict stock price movements accur…