Purpose This study presents a structured investigation of the most important causes for
delay in commercial real estate transactions. It assesses the potential of digital technologies …

We argue that financial risk managers should focus more strongly on developing forward-
looking early warning indicator systems for the North American real estate market. Based on …

This paper examines the relationship between news-based sentiment, captured through a
machine learning approach, and the US securitised and direct commercial real estate …

We construct a Google search-based measure of energy price uncertainty (ENPU) that
reflects oil, coal and natural gas price uncertainty. Using this index, we analyse the evolution …

Prediction of stock prices using time series analysis is quite a difficult and challenging task
since the stock prices usually depict random patterns of movement. However, the last …

Purpose–Recent research has found significant relationships between internet search
volume and real estate markets. This paper aims to examine whether Google search volume …

This paper proposes a new investor sentiment indicator that combines the use of principal
component analysis with web searches. This proposal provides economic meaning to the …

This study aims to explore whether the intensity of internet searches, according to the
Google Trends search volume index (SVI), is a predictor of changes in real estate prices …

In seeking to understand time variation in the rates of return earned by those who invest in
financial securities, researchers have uncovered various empirical regularities. Some are …

The phases of a crisis are critical to understanding its evolution. We construct an economic
agent-determined machine learning-based Google search index that associates search …