Asset Pricing Dynamics at ANREVOctober 19, 2015 / By
Today I am at the 7th Annual ANREV conference- this year in Singapore. It’s the leading conference for unlisted funds management in Asia Pacific, similar to INREV in Europe.
JLL has always been a big participant at ANREV and this year is no exception. We hosted the preconference drinks last night and had a big gathering of over 300 investment industry leaders. The talking point of the event were the big JLL banners with illustrations of real estate market cycles. As research thought leaders we often sit on panels and present new research at the conference. This year Dr David Rees presented to the exclusive Investor Day that takes place the day before the main event on the JLL asset pricing project undertaken with the World Economic Forum.
As part of the ongoing World Economic Forum project on real estate asset pricing led by David, we wrote a summary to explain how the physical characteristics of land and property impact the pricing cycle. It sets out a framework to explain the differing dynamics of the case studies prepared by the JLL research teams in Tokyo, Sydney, Shanghai, Mumbai & Bangalore, and Hong Kong. It’s an adaptation of Oakerson’s model which was developed to apply to common property resources and has applicability to commercial property, particularly here in Asia Pacific where some of our cities are constrained by physical features such as the sea on one side and hills on the other; or multiple ownership property.
To explain the model we developed the graphic illustration above. It shows land supply constraints on the left hand side, interacting with market rules and social customs in the middle. These market rules include formal rules like planning and location specific informal rules such as requiring substantial pre commitments in leasing before undertaking new development. The real estate market all takes place within the wider context of the macro environment. The interaction between land characteristics, formal and informal rules and the macro context are then filtered through the actions of people and the five forces that drive markets, including real estate markets. In addition to confidence, these are fairness, corruption, money illusion and stories. The combination of these multiple factors can trigger real estate asset pricing shifts.
One of the clear findings out of the original report was that no one size fits all in terms of explaining why a bubble can pop up in a market.
This diagram seeks to put in place a model framework that structures all the myriad of factors in the case studies into a single page.
For the full explanation of this diagram and to see the city specific diagrams show the real estate market case studies please click here.
For further information on the World Economic Forum project contact David Rees.