Modelling banking-hall yield for property investment

Tipping, Malvern and Newton, Roger (2015) Modelling banking-hall yield for property investment. Journal of Corporate Real Estate, 17 (1). pp. 4-25. ISSN 1463-001X

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Official URL: http://dx.doi.org/10.1108/JCRE-04-2014-0009

Abstract

Purpose – The study seeks to build a predictive model for the investment yield of British banking-halls. Design/methodology/approach – Empirical data of similar lots sold at previous auctions are subjected to statistical analyses utilizing a cross-sectional research design. The independent variables analysed are taken from a previous study using the same cases. Models are built using logistic regression and ANCOVA. Findings – Logistic regression generally generates better models than ANCOVA. A division of Britain on a north/south divide produces the best results. Rent is as good as lot size and price in modelling, but has greater utility, because it is known prior to auction. Research limitations/implications – Cases analyzed were restricted to lots let entirely as banking-halls. Other lots comprising premises only partially used as banking-halls might produce different results. Freehold was the only tenure tested. Practical implications – The study provides a form of predictive modelling for investors and their advisors using rent which is known in advance of any sale. Originality/value – The study makes an original contribution to the field, because it builds a predictive model for investment yields for this class of property. Further research may indicate if similar predictive models can be built for other classes of investment property. Keywords: Banking-hall; investment; portfolio; predictive framework; rent; yield; index. Article classification: Research paper.

Item Type: Journal Article
Keywords: Banking-hall, Investment, Portfolio, Predictive framework, Rent, Yield, Index
Faculty: Faculty of Science & Technology
Depositing User: Unnamed user with email malvern.tipping@anglia.ac.uk
Date Deposited: 16 Aug 2016 15:44
Last Modified: 01 Apr 2017 01:02
URI: http://arro.anglia.ac.uk/id/eprint/700679

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