Analyzing the performance of non-listed real estate funds: an panel data analysis

The rapid growth of non-listed real estate funds over the last several years has contributed towards establishing this sector as a major investment vehicle for gaining exposure to commercial real estate. Academic research has not kept up with this development, however, as there are still only a few published studies on non-listed real estate funds. This paper aims to identify the factors driving the total return over a seven-year period. Influential factors tested in our analysis include the weighted underlying direct property returns in each country and sector as well as fund size, investment style gearing and the distribution yield. Furthermore, we analyze the interaction of non-listed real estate funds with the performance of the overall economy and that of competing asset classes and found that lagged GDP growth and stock market returns as well as contemporaneous government bond rates are significant and positive predictors of annual fund performance.

Risk factors of European non-listed real estate fund returns

Acknowledgements: We thank INREV (the European Association for Investors in Non-Listed Real Estate Vehicles) for funding a previous version of this research and providing non-listed fund data as well as very useful comments. This version is published as Delfim, J.-C. and Hoesli, M., 2015, Risk Factor Analysis of European Non-Listed Real Estate Funds, Amsterdam: INREV. The usual disclaimer applies. We also thank three anonymous reviewers and the guest editor, Graeme Newell, for insightful remarks.

Non-normal real estate return distributions by property type in the UK

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD UK database over the period 1981 to 2003 than normally distributed risk models. This finding mirrors results in the US and Australia using identical methodology. Real estate investment risk is heteroskedastic, but the characteristic exponent of the investment risk function is constant across time – yet it may vary by property type. Asset diversification is far less effective at reducing the impact of non‐systematic investment risk on real estate portfolios than in the case of assets with normally distributed investment risk. The results, therefore, indicate that multi‐risk factor portfolio allocation models based on measures of investment codependence from finite‐variance statistics are ineffective in the real estate context

Non-normal real estate return distributions by property type in the U.K.

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD database over the period 1981 to 2003 than Normally distributed risk models, which mirrors results in the U.S. and Australia using identical methodology. Real estate investment risk is heteroscedastic, but the Characteristic Exponent of the investment risk function is constant across time yet may vary by property type. Asset diversification is far less effective at reducing the impact of non-systematic investment risk on real estate portfolios than in the case of assets with Normally distributed investment risk. Multi-risk factor portfolio allocation models based on measures of investment codependence from finite-variance statistics are ineffectual in the real estate context.

The performance effects of composition changes on sector specific stock indices: The case of European listed real estate

This paper examines the impact of changes in the composition of real estate stock indices, considering companies both joining and leaving the indices. Stocks that are newly included not only see a short-term increase in their share price, but trading volumes increase in a permanent fashion following the event. This highlights the importance of indices in not only a benchmarking context but also in enhancing investor awareness and aiding liquidity. By contrast, as anticipated, the share prices of firms removed from indices fall around the time of the index change. The fact that the changes in share prices, either upwards for index inclusions or downwards for deletions, are generally not reversed, would indicate that the movements are not purely due to price pressure, but rather are more consistent with the information content hypothesis. There is no evidence, however, that index changes significantly affect the volatility of price changes or their operating performances as measured by their earnings per share.

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

Joint Leverage and Maturity Choices in Real Estate Firms: The Role of the REIT Status

We explore the interdependence of leverage and debt maturity choices in Real Estate Investment Trusts (REITs) and unregulated listed real estate investment companies in the U.S. for the period 1973-2011. We find that the leverage and maturity choices of all listed real estate firms are interdependent, but in contrast to industrial firms, they are not made simultaneously. Across the different types of real estate firms considered, we find substantial differences in the nature of the relationship between leverage and maturity. Leverage determines maturity in non-REITs, whereas maturity is a determinant of leverage in REITs. We suggest that the observed differences reflect the effects of the REIT regulation, rather than solely being a function of real estate as the underlying asset class. We also present novel evidence that the relationship between leverage and maturity in both firm types can be used to moderate the effects of other exogenous financing policies.

Dynamic linkages of real estate and stock markets in Finland

Traditionally real estate has been seen as a good diversification tool for a stock portfolio due to the lower return and volatility characteristics of real estate investments. However, the diversification benefits of a multi-asset portfolio depend on how the different asset classes co-move in the short- and long-run. As the asset classes are affected by the same macroeconomic factors, interrelationships limiting the diversification benefits could exist. This master’s thesis aims to identify such dynamic linkages in the Finnish real estate and stock markets. The results are beneficial for portfolio optimization tasks as well as for policy-making. The real estate industry can be divided into direct and securitized markets. In this thesis the direct market is depicted by the Finnish housing market index. The securitized market is proxied by the Finnish all-sectors securitized real estate index and by a European residential Real Estate Investment Trust index. The stock market is depicted by OMX Helsinki Cap index. Several macroeconomic variables are incorporated as well. The methodology of this thesis is based on the Vector Autoregressive (VAR) models. The long-run dynamic linkages are studied with Johansen’s cointegration tests and the short-run interrelationships are examined with Granger-causality tests. In addition, impulse response functions and forecast error variance decomposition analyses are used for robustness checks. The results show that long-run co-movement, or cointegration, did not exist between the housing and stock markets during the sample period. This indicates diversification benefits in the long-run. However, cointegration between the stock and securitized real estate markets was identified. This indicates limited diversification benefits and shows that the listed real estate market in Finland is not matured enough to be considered a separate market from the general stock market. Moreover, while securitized real estate was shown to cointegrate with the housing market in the long-run, the two markets are still too different in their characteristics to be used as substitutes in a multi-asset portfolio. This implies that the capital intensiveness of housing investments cannot be circumvented by investing in securitized real estate.

Ownership Advantages in Cross-border Real Estate Development: Some Evidence from European Markets

Drawing upon European industry and country case studies, this paper investigates the scope and drivers of cross-border real estate development. It is argued that the real estate development process encompasses a diverse range of activities and actors. It is inherently localised, the production process is complex and emphermal, and the outputs are heterogeneous. It analyses a transactions database of European real estate markets to provide insights into the extent of, and variations in, market penetration by non-domestic real estate developers. The data were consistent with the expectation that non-domestic real estate developers from mature markets would have a high level of market penetration in immature markets. Compared to western European markets, the CEE real estate office sales by developers were dominated by US, Israeli and other EU developers. This pattern is consistent with the argument that non-domestic developers have substantial Dunning-type ownership advantages when entering immature real estate markets. However, the data also suggested some unexpected patterns. Relative to their GDP, Austria, Belgium, Denmark, Sweden, Netherlands and Israel accounted for large proportions of sales by developers. All are EU countries (except Israel) with small, open, affluent, highly traded economies. Further, the data also indicate that there may be a threshold where locational disadvantages outweigh ownership advantages and deter cross-border real estate development.

Can sentiment surveys pre-empt real estate market activities?

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting the demand and supply activities. Our focus lies on sector-specific surveys targeting the players from the supply-side of both residential and non-residential real estate markets. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework, we test the efficacy of these indices by comparing them with other coincident indicators in predicting real estate returns. Overall, our analysis suggests that sentiment indicators convey important information which should be embedded in the modeling exercise to predict real estate market returns. Generally, sentiment indices show better information content than broad economic indicators. The goodness of fit of our models is higher for the residential market than for the non-residential real estate sector. The impulse responses, in general, conform to our theoretical expectations. Variance decompositions and out-of-sample predictions generally show desired contribution and reasonable improvement respectively, thus upholding our hypothesis. Quite remarkably, consistent with the theory, the predictability swings when we look through different phases of the cycle. This perhaps suggests that, e.g. during recessions, market players’ expectations may be more accurate predictor of the future performances, conceivably indicating a ‘negative’ information processing bias and thus conforming to the precautionary motive of consumer behaviour.

Macro-economic and financial determinants of comovement across global real estate security markets

This paper models the determinants of integration in the context of global real estate security markets. Using both local and U.S. Dollar denominated returns, we model conditional correlations across listed real estate sectors and also with the global stock market. The empirical results find that financial factors, such as the relationship with the respective equity market, volatility, the relative size of the real estate sector and trading turnover all play an important role in the degree of integration present. Furthermore, the results highlight the importance of macro-economic variables in the degree of integration present. All four of the macro-economic variables modeled provide at least one significant result across the specifications estimated. Factors such as financial and trade openness, monetary independence and the stability of a country’s currency all contribute to the degree of integration reported.

Futures trading, spot price volatility and market efficiency: evidence from European real estate securities futures

In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naïve and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.

Low-frequency volatility of real estate securities in relation to macroeconomic risk

Real estate securities have a number of distinct characteristics that differentiate them from stocks generally. Key amongst them is that under-pinning the firms are both real as well as investment assets. The connections between the underlying macro-economy and listed real estate firms is therefore clearly demonstrated and of heightened importance. To consider the linkages with the underlying macro-economic fundamentals we extract the ‘low-frequency’ volatility component from aggregate volatility shocks in 11 international markets over the 1990-2014 period. This is achieved using Engle and Rangel’s (2008) Spline-Generalized Autoregressive Conditional Heteroskedasticity (Spline-GARCH) model. The estimated low-frequency volatility is then examined together with low-frequency macro data in a fixed-effect pooled regression framework. The analysis reveals that the low-frequency volatility of real estate securities has strong and positive association with most of the macroeconomic risk proxies examined. These include interest rates, inflation, GDP and foreign exchange rates.

Diversification benefits for a Finnish non-industrial private forest investor: Real Estate Investment Trusts in the USA

This thesis examined both domestic and international forest investment options for a Finnish non-industrial private forest investor. The focus was on forest-based investment instruments. The influence of movements of currency exchange rates on foreign returns were also taken into account. Annual data from 1995 to 2011 was used. The main portfolio optimization model in this study was the Mean-Variance model but the results were also validated by using the Value at Risk and Expected Shortfall models. In addition, the exchange rate risk hedging was established by using one-week-maturity forward contracts. The results suggested that 75 % of the total wealth should be invested in Finnish private forests and the rest, 25 %, to a US REIT, in this case Rayonier. With hedging, the total return on the portfolio was 7.21 % (NIPF 5.3%) with the volatility of 6.63 % (NIPF 7.9%). Taxation supported US investments in this case. As a conclusion, a Finnish private forest investor may, as evidenced, benefit in diversifying a portfolio using REITs in the US.