In mainstream economics and finance literature, market sentiment is considered “irrational”. This leads to significant challenges in capturing the effect of sentiment on economic relationships. Real estate is even more complex due to the fact that the sector exhibits several market inefficiencies. The purpose of this paper is to explore the literature and present a simple test for the potential of using three different sentiment indicators to improve a basic cap rate model. The authors establish the case using commercial real estate (CRE) data for London West End.
The three indicators differ in their underlying source and method. The authors used orthogonalisation and principal component analysis for a macroeconomic sentiment indicator. Furthermore, online search volume data have been used to mirror the market sentiment for the London West End market. Finally, textual analysis based on word lists has been applied to corpus of market reports.
The results indicate considerable improvement in the authors’ ability to capture the effect of sentiment. Furthermore, the consideration of a human factor leads to improvement in the basic yield model.
The methods suggest that sentiment extracted from more forward-looking sources, such as online searches, could be a significant information gain for investors, lenders or other market participants. The additional information could be used to adjust their behaviour within the market.
To the authors’ knowledge, this is the first study that applies textual analysis to market reports for the CRE market in the UK.
Heinig, S. and Nanda, A. (2018), "Measuring sentiment in real estate – a comparison study", Journal of Property Investment & Finance, Vol. 36 No. 3, pp. 248-258. https://doi.org/10.1108/JPIF-05-2017-0034Download as .RIS
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