An ever-increasing share of human interaction, communication, and culture is recorded as
digital text. We provide an introduction to the use of text as an input to economic research …

Financial Literacy plays a crucial role in individuals' decision-making process. Existing
studies have shown that lower level of financial literacy lead to irrational financial decision …

We create a newspaper-based Equity Market Volatility (EMV) tracker that moves with the VIX
and with the realized volatility of returns on the S&P 500. Parsing the underlying text, we find …

We study how researchers can apply machine learning (ML) methods in finance. We first
establish that the two major categories of ML (supervised and unsupervised learning) …

Based on high-frequency data for more than fifty commodities, currencies, equity indices,
and fixed-income instruments spanning more than two decades, we document strong …

We introduce a new text-mining methodology that extracts sentiment information from news
articles to predict asset returns. Unlike more common sentiment scores used for stock return …

We propose an approach to measuring the state of the economy via textual analysis of
business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we …

We propose an approach to measuring the state of the economy via textual analysis of
business news. From the full text content of 800,000 Wall Street Journal articles for 1984 …

In this manuscript, we propose a Machine Learning approach to tackle a binary classification
problem whose goal is to predict the magnitude (high or low) of future stock price variations …

Using a unique dataset of fake stock promotion articles prosecuted by the Securities and
Exchange Commission, we examine the impact of fake news. In addition, we use a linguistic …