European Real Estate Society
This presentation is the property of its rightful owner.
Sponsored Links
1 / 22

European Real Estate Society Annual Conference Vienna 2013 The City of London Office Bias by Stephen Lee Cass Business School, City University London PowerPoint PPT Presentation


  • 49 Views
  • Uploaded on
  • Presentation posted in: General

European Real Estate Society Annual Conference Vienna 2013 The City of London Office Bias by Stephen Lee Cass Business School, City University London. Introduction. It is well known that UK institutional investors have a bias towards the City of London office market.

Download Presentation

European Real Estate Society Annual Conference Vienna 2013 The City of London Office Bias by Stephen Lee Cass Business School, City University London

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


European real estate society annual conference vienna 2013 the city of london office bias by stephen lee cass business school city university london

European Real Estate Society

Annual Conference

Vienna 2013

The City of London Office Bias

by

Stephen Lee

Cass Business School, City University London


Introduction

Introduction

It is well known that UK institutional investors have a bias towards the City of London office market.

Yet studies show that investment outside the City of London offers higher returns, lower risks and larger rental growth.

In addition, the that initial yields are lower in the City of London than in almost every other market, i.e. institutional investors over-price City offices and under-price almost all other office markets.

An economically sensible way to measure this bias is to calculate the additional required return on offices outside the City of London necessary to tilt the intuition’s allocation away from that observed.


European real estate society annual conference vienna 2013 the city of london office bias by stephen lee cass business school city university london

Data

Summary Statistics: Quarterly Data 2001-2012


Methodology

Methodology

The usual asset allocation model is as follows:

An alternative approach, and the one adopted here, is to calculate the expected returns implied by the observed weights wobs and derive the expected return vector m, given the historic variance-covariance matrix Sbut allow the relative risk parameter λ to be estimated by the optimisation process such that the expected return of the City equals that calculated from historical data.


Data and methodology

Data and Methodology

Annualised City of London Office Bias: Bps


Possible explanations for the city bias

Possible Explanations for the City Bias

Liquidity

Quality

Lot Size

Familiarity

Norms


Liquidity

Liquidity?

According to Key et al (1998) “… ‘illiquidity’ tops the list of things property investors dislike about property ...”.

Indeed, Lizieri (2009) postulates that the observed holdings in property markets maybe driven “by need for liquidity … over and above optimal risk-adjusted returns”.

That is, investors who value liquidity may be willing to deviate from portfolio allocations derived from MPT.

In other words, while liquidity risk may be low for investors who have already “taken the plunge” into markets outside the City issues with illiquidity may prevent a subset of investors from ever investing in such markets.

So is that it?


Liquidity1

Liquidity?

Average Quarterly Transaction Rate 2001-2012


Liquidity2

Liquidity?

Average Purchases and Sales: 2001-2012


Liquidity3

Liquidity?

Average Time to Transact

McNamara (1998)


Quality

Quality?

A prerequisite for institutional investment in standing property is for stock to be available and of “investible” quality (Key and Law, 2005).

Indeed, Malpezzi and Shilling (2000) find that real estate investors tilt their real estate holdings towards quality.

While, Henneberry et al (2004) argue that the “stock of office properties in London is likely to be of significantly better quality than elsewhere”

So is that it?


Quality1

Quality?

Number of tenants, Property Size: End 2008

Wiak and Key (2009) Real World Conference,

More tenants, Bigger size


Quality2

Quality?

Fewer break clauses


Lot size

Lot Size?

One important quality investment characteristic is lot size for a number of reasons.

Economies of scale: i.e. the management costs of one property with a value of £50m are considerably less than the management costs of 10 properties of £5m

Larger properties can have a greater number of tenants, which lessens the impact if one leaves.

This suggests that institutions would benefit from holding fewer but larger properties.

Indeed, the average number of properties in institutional portfolios has declined over time.

From 93 in 1981 to 40 by 2010.

So is that it?


Size and age

Size and Age?

City Office Portfolios are Younger and Bigger

81% by Value post 80 buildings and Average size >£30m

Source: IPD Annual Index 2011

Average data 2001-2011


Familiarity

Familiarity?

A number of researchers report that familiarity is particular important to investors.

Hence another reason for the City office bias is the relative optimism investors have towards a familiar market.

In other words, investor’s have limited information about markets they are unfamiliar with and so display a preference for assets with which they are more familiar, despite the gains from diversification into the “unknown.”

So is that it?


Familiarity1

Familiarity?

A main criticism of the limited information explanation is that it only fits the data when investors forecast higher returns for the City offices than the rest of the office markets in the UK.

But there must be times in which City investors actually forecast lower returns for the City of London office market than the rest of the UK.

During these times, the City office portfolio should be tilted toward the other markets.

However, as shown in Table 1 the bias towards City offices has remained stable and persists over time.


Norms benchmarks

Norms/Benchmarks?

Tversky and Kahneman (1974) suggest that investors may determine future allocation by initially anchoring on their current allocation.

Thus, if the initial allocation were 3%, then a 6% allocation would be regarded as a fairly extreme deviation from policy, i.e. a doubling of their current exposure.

Such conservatism is based on norms, traditions and habits indoctrinated by years of customs and so there is a “tendency of groups to stick to established patterns” (Thaler and Sunstein, 2009).

This also resonates with Lizieri’s (2009) “spatial prism”.

So is that it?


Norms

Norms?

In the context of a City of London bias this would mean that investors are City biased because their peer group is City biased.

In other words, managers take a high risk if they deviation for benchmark weights and so will have a distinct prejudice against certain regions and so there will be a very low exposure to such markets.

Graff and Young (1996) support of this view in the US.


Conclusions

Conclusions

This paper seeks to test the hypothesis that institutional investment in the City of London office market does not conform to the assumption of economic rationality by using a simple asset allocation model.

We find that the additional return required for office markets outside the City necessary to tilt the intuition’s allocation away from that observed is in excess of 300 bps per annum in a number of markets.

These implied shadow or management costs seem well above any reasonable estimates that would justify investment in such markets.

In other words, it appears to provide evidence of irrationality (in the strict traditional economic sense) in the behaviour of institutional investors.


Conclusions1

Conclusions

However, the literature suggests that a wider spectrum of factors need to be examined to explain the asset allocation decisions of fund managers, beyond traditional proxy for risk (SD).

Therefore we looked at 5 factors

  • Liquidity

  • Quality

  • Lot Size

  • Familiarity

  • Norms

    but find none that seems to provide a satisfactory explanation


European real estate society annual conference vienna 2013 the city of london office bias by stephen lee cass business school city university london

European Real Estate Society

Annual Conference

Vienna 2013

The City of London Office Bias

 Any Questions?


  • Login