Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

We developed a model-free Bayesian extraction procedure for the stochastic discount factor under a yield curve prior. Previous methods in the literature directly or indirectly use some particular parametric asset-pricing models such as with long-run risks or habits as the prior. Here, in...

This paper provides a unique COVID-19 disclosure measurement and investigates the association between the level of COVID-19 disclosure and uncertainty within annual reports for UK FTSE-All share non-financial firms. We used automated textual analysis to score the sampled annual reports. The...

The close relationship between governments and their central banks generates risks for both partners. This paper presents an original qualitative empirical approach based on textual analysis of the United States of America, China, and their Central Banks’ respective communications. These...

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current...

Tweets seem to impact diverse assets, especially during stressful periods. However, their interrelations during stressful events may change. Cryptos are apparently more sensitive to the sentiment spread by tweets. Therefore, a construct could be formed to study such complex interrelation during...

Unprecedented opportunities have been brought by advancements in machine learning in the prediction of the economic success of movies. The analysis of movie title keywords is one promising but rarely investigated direction of study. To address this gap, we performed a text mining and exploratory...

In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the...

This paper investigates the impact of annual report readability on the corporate bond market. My findings indicate that in the US corporate bond market, firms with less readable annual reports tend to have higher credit spreads, higher credit spread volatilities, higher transaction costs, higher...