Can Linear Predictability Models Time Bull and Bear
Real Estate Markets? Out-of-Sample Evidence
from REIT Portfolios
Daniele Bianchi ·Massimo Guidolin
Published online: 6 April 2013

Abstract

A recent literature has shown that REIT returns contain strong evidence of
bull and bear dynamic regimes that may be best captured using nonlinear econometric
models of the Markov switching type. In fact, REIT returns would display regime
shifts that are more abrupt and persistent than in the case of other asset classes. In
this paper we ask whether and how simple linear predictability models of the vector
autoregressive (VAR) type may be extended to capture the bull and bear patterns
typical of many asset classes, including REITs. We find that nonlinearities are so
deep that it is impossibile for a large family of VAR models to either produce similar
portfolio weights or to yield realized, ex-post out-of-sample long-horizon portfolio
performances that may compete with those typical of bull and bear models. A typical
investor with intermediate risk aversion and a 5-year horizon ought to be ready to
pay an annual fee of up to 5.7 % to have access to forecasts of REIT returns that

International Direct Real Estate Risk Premiums
in a Multi-Factor Estimation Model
David Kim Hin Ho & Kwame Addae-Dapaah &
John L. Glascock
Published online: 3 July 2014

Abstract

We estimate international risk premiums for North and South Asia and US
direct real estate by using a pooled-panel multi-factor least squares model. Data for the
paper are from JLL REIS-Asia and the Russell-NCREIF Property Indexes. Our results,
based on the Geltner and Miller (2007) 1st and 4th order autoregressive de-smoothing
models, affirm the existence of appraisal smoothing in the direct real estate market
returns. Secondly, our findings affirm that the true historical volatility of autoregressive
lagged de-smoothed returns is a reasonable estimate of international direct real estate
risk premiums. Thirdly, we find that changes in macroeconomic and real estate
variables explain the office and retail returns more than the residential returns. There
is also a high vacancy rate risk premium that we attribute to country-specific, institutional
environmental factors. Furthermore, the South Asia direct real estate risk premium
is found to be higher than that for North Asia. Moreover the risk premiums for
North and South Asia are higher than that for the US. Finally, our results show that
appraisal smoothed returns significantly underestimate the international direct real
estate risk premiums for the sampled Asia markets and the US.

Related Party Transactions and Firm Value: Evidence
from Property Markets in Hong Kong, Malaysia
and Singapore
David H. Downs1 & Joseph T. L. Ooi2 &
Woei-Chyuan Wong3 & S. E. Ong2

Abstract

This paper offers new evidence as to how RPTs can be value enhancing for
minority shareholders. In doing so, we address an ongoing theoretical tension in the
related party transaction (RPT) literature by focusing on real estate investment trusts
(REITs) in Asia. The empirical evidence is mixed in the corporate finance literature on
whether RPTs create or destroy firm value. On average, REITs in our sample engaged
in RPTs amounting to 5.4 % of total assets, annually, between 2003 and 2010. This is
not a trivial amount and is nearly double the 2.8 % RPT rate for U.S. industrial firms.
We identify three main channels for REIT RPTs: real estate asset acquisitions from
related parties (57.4 %), income earned from related parties (22.2 %) and management
fees paid to related parties (14.8 %). The identification strategy we employ relies on
two distinct methodologies when examining RPTs and firm value: a multivariate
regression approach and, secondly, an exogenous wealth effects test for RPT announcements. Overall, the results suggest that REIT managers and sponsors do not
expropriate wealth from their minority shareholders through RPTs. We find evidence
that an ad hoc acquisitions pipeline from sponsor to REIT generally drives the value

Time-Varying Betas of US REITs from 1972 to 2013
Tien Foo Sing1 & I-Chun Tsai 2 & Ming-Chi Chen3

Abstract

This study estimates the time-varying REIT betas with a structural
time series model using monthly REIT return data for the periods from 1972 to
2013. Based on the FTSE-NAREIT return indices for the equity REIT (EREIT)
and mortgage REIT (MREIT), we found corroborative evidence of the temporal
declines in the betas of the two REITs up to 1999. The time-varying beta
characteristics of the two REIT betas are fundamentally different in the 2000s.
While the MREIT betas continued to decline, the EREIT betas showed a sharp
reversal of the downward trend. Coinciding with the low interest regime in the
US, EREITs used more external debt to fund new acquisitions and development
activities, and as a result, the EREIT betas increased sharply in 2000s. The
EREIT betas hit the peak in 2009; and declined thereafter when active
deleveraging occurred in the market. Using firm level data, we construct two
leverage-sorted EREIT portfolios, and our empirical results do not reject the
leverage effects on time-varying EREIT betas. However, we find that the
leverage effect is not triggered by the declines in stock prices as proposed in
the finance literature.

Cornish-Fisher Expansion for Commercial Real Estate
Value at Risk
Charles-Olivier Am´ed´ee-Manesme ·
Fabrice Barth´el´emy · Donald Keenan
Published online: 5 July 2014

Abstract

The computation of Value at Risk has traditionally been a troublesome
issue in commercial real estate. Difficulties mainly arise from the lack of appropriate
data, the non-normality of returns, and the inapplicability of many of the traditional
methodologies. As a result, calculation of this risk measure has rarely been done in
the real estate field. However, following a spate of new regulations such as Basel
II, Basel III, NAIC and Solvency II, financial institutions have increasingly been
required to estimate and control their exposure to market risk. As a result, financial
institutions now commonly use “internal” Value at Risk (VaR) models in order
to assess their market risk exposure. The purpose of this paper is to estimate distribution
functions of real estate VaR while taking into account non-normality in
the distribution of returns. This is accomplished by the combination of the Cornish-
Fisher expansion with a certain rearrangement procedure. We demonstrate that this
combination allows superior estimation, and thus a better VaR estimate, than has
previously been obtainable. We also show how the use of a rearrangement procedure
solves well-known issues arising from the monotonicity assumption required for the
Cornish-Fisher expansion to be applicable, a difficulty which has previously limited the useful of this expansion technique. Thus, practitioners can find a methodology
here to quickly assess Value at Risk without suffering loss of relevancy due to any
non-normality in their actual return distribution. The originality of this paper lies
in our particular combination