Refining the real estate pricing model

Abstract

Investment theory dictates that capitalisation (cap) rates for freehold real estate should be determined by the risk free nominal rate of return plus the risk premium (RP) less the expected growth rate, with an allowance for depreciation. However, importing the concept of the RP from the capital markets fails to guide investors through the complexities of the asset, or enable exploration of purchaser preferences and behaviour. A refined pricing model for real estate is proposed, based on a concept termed a risk scale, to distinguish between macro (market) and micro (stock) determinants of risk and growth within the RP. This pricing model is estimated for a major global investment market, using a cross-sectional intertemporal framework, with a dataset of 497 transactions in the London office sector over 2010Q2-2012Q3. Average cap rates are estimated at just over 5%, with asset-specific attributes dominating yield determination, with submarket quality and tenant covenant most important; and unexpired I investors bought at lower cap rates, despite the ongoing economic and financial instability of the study period. Improving understanding of pricing behaviour and market transparency is important and may be advanced through the pricing model. Key wordsProperty investment, office market, London, capitalisation rates, risk premium. 2Refining the real estate pricing model IntroductionThe nature and behaviour of commercial investors have radically altered in the wake of the globalisation and liberalisation of capital and investment markets during the second half of the 20 th Century and the first few years of the 21 st . A consequence of these changes has been that the ownership of larger, more valuable real estate has shifted from small local entrepreneurs to major real estate companies, financial institutions and funds, both national and international, with banks acting as a major source of finance for much of this change. Subsequently, commercial investment real estate pricing has developed within an increasingly sophisticated, analytical and global environment.However, the relative lack of transaction volumes in the direct real estate market, and the fact that many transactions are not in the public domain, has restricted analysis of pricing and investor behaviour in the acquisition and sale process, in performance measurement and in bank lending decision-making. This is significant given that G pricing model, used within real estate markets, has been adopted from the capital markets and might struggle to cope with the unique and complex nature of the asset. The aim of this study is to redress this imbalance by revisiting and extending the theoretical pricing model to fully reflect both the complex characteristics of the real estate market and of the asset attributes that drive returns, to provide a framework for systematic asset pricing.This new, explicit framework is operationalised in the second half of the paper, to provide an example of its utility by empirically estimating the perceived risk attached to...

The implied internal rate of return in conventional residual valuations of development sites

“…This is in contrast to the situation for property investments where the formation of target return rates is relatively well understood (see Crosby et al, 2016) and data on yields from transactions allows expected rates of return to be inferred if they are not disclosed explicitly. Meanwhile, achieved rates of return for investment properties at country, sector and segment level are published by MSCI for many mature property markets based on the holdings of large institutional investors.…”

Measuring and Assessing the Impact of the Global Economic Crisis on European Real Property Market

“…Also, an analysis of prices and their indexes appears vital from the point of view of research into the real estate market (cf. the works by Case & Quigley, 1991;Netzell, 2012;Kokot, 2014;Crosby, Jackson, & Orr, 2016), value of the construction production (Stasiak-Betlejewska & Potkany, 2015;Ofori, 2007), as well as employment and its evident impact on the economy in the theory of economy (Keynes, 2003).…”

Only the Best? Exploring Cross-Border Investor Preferences in US Gateway Cities

“…Multilevel modelling of datasets featuring different cities and submarkets has been applied previously in hedonic studies of residential real estate prices. 4 Its application in a commercial real estate context has been less common, but Crosby et al (2016) use multilevel modelling to explain variation in office capitalization rates while Yildirim (2008) uses multilevel modelling in the context of the incidence and timing of default for CMBS loans. In Yildirim, region and property type are identified as the levels assumed to affect incidence of default prior to consideration of loan-specific attributes.…”

“…Finally, Crosby et al (2016) examined pricing for a sample of just under 500 office buildings in Central London during 2010-12. Although not a central feature of their study, the authors included variables in their modelling that related to the national origin and international experience of the purchasers in each transaction.…”