... the Herfindahl–Hirschman Index (HHI). Using over 30,000 monthly REIT bond yield spreads from 2010 to 2023, we combine machine learning (ML) methods (artificial neural network and accumulated local effect plots) and ordinary least squares regression with polynomial terms. Findings We find a local real estate...

...Marcelo Cajias; Anna Freudenreich Purpose This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets. Design/methodology/approach The random survival forest approach is introduced to the real estate market. The most important...

... Rents Generalized additive model Machine learning Air pollution is one of the most significant threats worldwide, causing substantial environmental and social problems, particularly in megacities where its impacts are most acutely felt. The European Environment Agency (2022) published...

... developments in time series forecasting using machine learning and deep learning methods offer an opportunity to update traditional univariate forecasting frameworks. Design/methodology/approach With the aim to extend research on univariate rent forecasting a hybrid methodology combining both ARIMA...

... characteristics. Recently, Machine Learning (ML) techniques, which are a subset of Artificial Intelligence, are gaining momentum in solving complex, non-linear problems like house price forecasting. Hence, this study deployed three popular ML techniques to predict dwelling prices in two cities in Italy. Design...

... style and culture. Originality/value The introduction of artificial intelligence/machine learning (AI/ML), blockchain, virtual reality, tablets, cell phones, applications, 5G, etc. is putting pressure on real estate organisations to change. These changes are long overdue and the future, modern real...

.... Marcelo Cajias can be contacted at: marcelocajias@hotmail.com 05 06 2020 10 06 2020 10 06 2020 © Emerald Publishing Limited 2020 Emerald Publishing Limited Licensed re-use rights only Econometrics Artificial intelligence Hedonic models Machine learning Every real...

... extraction through machine learning algorithms is demonstrated. Preferred sources for key information of technical due diligence reports are presented. The paper concludes with challenges towards an automated information extraction in due diligence processes. Design/methodology/approach The comprehensive...

... compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis. Design/methodology/approach All tests comparing regression...