The appraisal of data centres: deconstructing the cash flow

[thumbnail of 0407.pdf]
Preview
Text - Published Version
· Please see our End User Agreement before downloading.
| Preview

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

McAllister, P. and Loizou, P., (2007) The appraisal of data centres: deconstructing the cash flow. Working Papers in Real Estate & Planning. 04/07. Working Paper. University of Reading, Reading. pp23.

Abstract/Summary

This paper analyses the appraisal of a specialized form of real estate - data centres - that has a unique blend of locational, physical and technological characteristics that differentiate it from conventional real estate assets. Market immaturity, limited trading and a lack of pricing signals enhance levels of appraisal uncertainty and disagreement relative to conventional real estate assets. Given the problems of applying standard discounted cash flow, an approach to appraisal is proposed that uses pricing signals from traded cash flows that are similar to the cash flows generated from data centres. Based upon ‘the law of one price’, it is assumed that two assets that are expected to generate identical cash flows in the future must have the same value now. It is suggested that the expected cash flow of assets should be analysed over the life cycle of the building. Corporate bond yields are used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds.

Item Type Report (Working Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/27051
Divisions Henley Business School > Real Estate and Planning
Publisher University of Reading
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar