Discussion In broad terms, the authors assess whether (and to what degree) social-media
sentiment and news sentiment lend insight on market activity that is not already captured in …

We extract commodity‐level sentiment from the Twittersphere in 2009–2020. A long–short
strategy based on sentiment shifts more than doubles the Sharpe ratio of extant commodity …

The author uses a broad set of news and social media sources to infer sentiment about the
global equity market. The author evaluates the contemporaneous and lagged relationship …

Nowadays, the social media play a central role not only in “de-asymmetrizing” the
information between firms and investors but also in influencing the emotional response to …

We examine the mechanism by which social media sentiment affects stock prices.
Specifically, we assess the impact of Twitter feeds on stock returns at the intraday level. We …

This article aims to provide information on how networks gauge and visualize complex
interactions and relationships between assets, factors, or other economic variables. The …

In this study, we predict next-day movements of stock end-of-day implied volatility using
random forests. Through an ablation study, we examine the usefulness of different sources …

Using machine learning and alternative data for the prediction of financial markets has been
a popular topic in recent years. Many financial variables such as stock price, historical …

Recent natural language processing (NLP) breakthroughs have proven effective for
addressing many language-directed tasks, such as completing sentences and addressing …

The determinants of fear gauge from March 2005 to September 2019 are empirically
examined with attention to the single equity volatility index (VIX). This study utilized Poisson …