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This paper studies diversification and value in the investment portfolios of (non-listed) Real Estate Investment Funds (REIFs) exploring how the value of diversification is captured by the market and by investors (beyond reported valuations).

We apply the Herfindahl-Hirschman Index (HHI) to study the level of concentration versus diversification in the investment portfolios of REIFs (both in terms of segment and geographical diversification). We use a dataset from INREV with data from 62 investment portfolios, with an average of 86 REIFs per portfolio for the period of 2008–2020 (to study segment diversification). We use a second dataset from INREV with data from 30 investment portfolios with an average of 79 REIFs per portfolio for the period of 2005–2020 (to study geographical diversification). We employ a cluster analysis approach to identify common features among the investment funds.

We conclude that (segment diversified) portfolios with higher degrees of leverage exhibit higher income yields, albeit diversification is captured indirectly through asset choices – more diversified portfolios tend to exhibit a stronger risk and return relationship. Also, geographical diversification creates value (more significantly by for the correct combination of countries carefully choosing what different geographies to group in the diversified portfolio).

One limitation of our study is that our portfolios are funds of funds, since the available data could not reach the asset detail, but we believe this does not compromise our results.

Diversification leads to higher risk-adjusted returns which suggests that properties may be undervalued (market value) in the framework of the Gordon Model, contrary to expectations (regarding investment value).

Investors capture the value of diversification differently, suggesting a gap between market value and investment value that can be explored.

This paper investigates the relationship between the sustainable finance disclosure regulation (SFDR) and the performance of unlisted real estate funds.

While existing literature has primarily focused on the impact of voluntary sustainability disclosure, such as certifications or reporting standards, this study addresses a significant research gap by constructing and analyzing the financial J-Curve of 40 funds under the SFDR. The authors employ a panel regression analysis to examine the effects of different SFDR categories on fund performance.

The findings reveal that funds categorized under Article 8 of the SFDR do not exhibit significantly poorer performance compared to funds categorized under Article 6 during the initial phase after launch. On average, Article 8 funds even demonstrate positive returns earlier than their peers. However, the panel regression analysis suggests that Article 8 funds slightly underperform when compared to Article 6 funds over time.

While investors may not anticipate lower initial returns when opting for higher SFDR categories, they should nevertheless be aware of the limitations inherent in the existing SFDR labeling system within the unlisted real estate sector.

To the best of our knowledge, this study represents the first quantitative examination of unlisted real estate fund performance under the SFDR. By providing unique insights into the J-Curves of funds, our research contributes to the existing body of knowledge on the impact of sustainability regulations in the financial sector.

Our aim in this study is to investigate the relative importance of the economic policy uncertainty and of the geopolitical risk on U.S. REITs (Real Estate Investment Trusts) returns with a special focus on the different real estate sectors.

We use an augmented Fama-French (1993)’s asset pricing model, including economic policy uncertainty indices (EPU), introduced by Baker et al. (2016), and geopolitical risk indices (GPR) recently developed by Caldara and Iacoviello (2022), to price the potential risk factors for U.S. Nareit indices returns. To obtain robust economic results, we correct for the problems of errors-in-variables in linear asset pricing models; we advocate the use of higher moments estimators as instruments in a generalized method of moments (GMM) framework.

Our results report that economic policy uncertainty (EPU), and geopolitical risk (GPR) are priced for the different Nareit sectors for the last three decades. The GPR index stands as a relevant risk factor. The coefficient estimates are low compared to Fama-French risk factors. They are higher for Shopping Centers, Retail and Region Malls and lower for Health Care and Lodging/Resorts. EPU indices are also priced and less statistically significant. Health Care sector, followed by Shopping Centers and Retail are the most policy-sensitive sectors.

In their “2023–2024 Top Ten Issues Affecting Real Estate” “political unrest and global economic health” is ranked 1 issue by the Counselors of Real Estate. Our results report that economic policy uncertainty and geopolitical risk are priced for the different Nareit sectors. They suggest implications for investors, insurers, bankers, policymakers and other stakeholders. The geopolitical risk index (GPR) stands as a relevant and significant risk factor for REITs returns.

Based on parsimonious robust asset pricing models, the results shed a new light on the relative importance of geopolitical risk and economic policy uncertainty in the real estate sector, with a special focus on the different U.S. REITs sectors. They suggest possible implications for investors, insurers, bankers, policymakers and other stakeholders in a context marked by higher uncertainty shocks and geopolitical risks.

Healthcare property has become an important alternate property sector in recent years for many international institutional investors. The purpose of this paper is to assess the risk-adjusted performance, portfolio diversification benefits and performance dynamics of French healthcare property in a French property portfolio and mixed-asset portfolio over 1999–2020. French healthcare property is seen to have different performance dynamics to the traditional French property sectors of office, retail and industrial property. Drivers and risk factors for the ongoing development of the direct healthcare property sector in France are also identified, as well as the strategic property investment implications for institutional investors.

Using annual total returns, the risk-adjusted performance, portfolio diversification benefits and performance dynamics of French direct healthcare property over 1999–2020 are assessed. Asset allocation diagrams are used to assess the role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio. The role of specific drivers for French healthcare property performance is also assessed. Robustness checks are also done to assess the potential impact of COVID-19 on the performance of French healthcare property.

French healthcare property is shown to have different performance dynamics to the traditional French property sectors of office, retail and industrial property. French direct healthcare property delivered strong risk-adjusted returns compared to French stocks, listed healthcare and listed property over 1999–2020, only exceeded by direct property. Portfolio diversification benefits in the fuller mixed-asset portfolio context were also evident, but to a much lesser extent in a narrower property portfolio context. Importantly, this sees French direct healthcare property as strongly contributing to the French property and mixed-asset portfolios across the entire portfolio risk spectrum and validating the property industry perspective of healthcare property being low risk and providing diversification benefits in a mixed-asset portfolio. However, this was to some degree to the loss or substitution of traditional direct property exposure via this replacement effect. French direct healthcare property and listed healthcare are clearly shown to be different channels in delivering different aspects of French healthcare performance to investors. Drivers of French healthcare property performance are also shown to be both economic and healthcare-specific factors. The performance of French healthcare property is also shown to be different to that seen for healthcare property in the UK and Australia. During COVID-19, French healthcare property was able to show more resilience than French office and retail property.

Healthcare property is an alternate property sector that has become increasingly important in recent years. The results highlight the important role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio, with French healthcare property having different investment dynamics to the other traditional French property sectors. The strong risk-adjusted performance of French direct healthcare property compared to French stocks, listed healthcare and listed property sees French direct healthcare property contributing to the mixed-asset portfolio across the entire portfolio risk spectrum. French healthcare property’s resilience during COVID-19 was also an attractive investment feature. This is particularly important, as many institutional investors now see healthcare property as an important property sector in their overall portfolio; particularly with the ageing population dynamics in most countries and the need for effective social infrastructure. The importance of French direct healthcare property sees direct healthcare property exposure accessible to investors as an important alternate real estate sector for their portfolios going forward via both non-listed healthcare property funds and the further future establishment of more healthcare REITs to accommodate both large and small institutional investors respectively. The resilience of French healthcare property during COVID-19 is also an attractive feature for future-proofing an investor’s portfolio.

This paper is the first published empirical research analysis of the risk-adjusted performance, diversification benefits and performance dynamics of French direct healthcare property, and the role of direct healthcare property in a French property portfolio and in a French mixed-asset portfolio. This research enables empirically validated, more informed and practical property investment decision-making regarding the strategic role of French direct healthcare property in a portfolio; particularly where the strategic role of direct healthcare property in France is seen to be different to that in the UK and Australia via portfolio replacement effects. Clear evidence is also seen of the drivers of French healthcare property performance being strongly influenced by healthcare-specific factors, as well as economic factors.

The aim of this study is to measure portfolio diversification benefits of the Turkey-based equity investors into top trading partner countries. Portfolio diversification benefits are analyzed from the viewpoint of two types of investors in Turkey: conventional equities investors and Islamic equity investors.

In order to evaluate the time-varying correlations of the trading partner country's stock index returns with the Turkish stock index returns, the multivariate-generalized autoregressive conditional heteroskedasticity–dynamic conditional correlation (GARCH-DCC) is applied based on daily data covering 13 years' period between January 22, 2008 and January 22, 2021.

The results revealed that the US stock indices provide the most diversified benefit for both conventional and Islamic Turkey-based equity investors. In general, Islamic indices exhibit relatively lower correlation with trading partners than conventional indices. Turkey and Russia are recorded as the most volatile indices.

The diversification potential in trading partners for Turkey-based Islamic equity investors has not been studied yet. This study is to fill in this gap in the literature and to give fruitful insights to both conventional and Islamic investors.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.

The purpose of this study is to explore the intricate relationship between oil prices, house prices in the UK and Norway, and the mediating role of gold and stock prices in both the short- and long-term, unraveling these complex linkages by employing an empirical approach.

This study benefits from a comprehensive set of econometric tools, including a multiequation vector autoregressive (VAR) system, Granger causality test, impulse response function, variance decomposition and a single-equation autoregressive distributed lag (ARDL) system. This rigorous approach enables to identify both short- and long-run dynamics to unravel the intricate linkages between Brent oil prices, housing prices, gold prices and stock prices in the UK and Norway over the period from 2005:Q1 to 2022:Q2.

The findings indicate that rising oil prices negatively impact house prices, whereas the positive influence of stock market performance on housing is more pronounced. A two-way causal relationship exists between stock market indices and house prices, whereas a one-way causal relationship exists from crude oil prices to house prices in both countries. The VAR model reveals that past housing prices, stock market indices in each country and Brent oil prices are the primary determinants of current housing prices. The single-equation ARDL results for housing prices demonstrate the existence of a long-run cointegrating relationship between real estate and stock prices. The variance decomposition analysis indicates that oil prices have a more pronounced impact on housing prices compared with stock prices. The findings reveal that shocks in stock markets have a greater influence on housing market prices than those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

This study may have several limitations. First, the model does not include all relevant macroeconomic variables, such as interest rates, unemployment rates and gross domestic product growth. This omission may affect the accuracy of the model’s predictions and lead to inefficiencies in the real estate market. Second, this study does not consider alternative explanations for market inefficiencies, such as behavioral finance factors, information asymmetry or market microstructure effects. Third, the models have limitations in revealing how predictors react to positive and negative shocks. Therefore, the results of this study should be interpreted with caution.

These findings hold significant implications for formulating dynamic policies aimed at stabilizing the housing markets of these two oil-producing nations. The practical implications of this study extend to academics, investors and policymakers, particularly in light of the volatility characterizing both housing and commodity markets. The findings reveal that shocks in stock markets have a more profound impact on housing market prices compared with those in oil or gold prices. Consequently, house prices exhibit a stronger reaction to general financial market indicators than to commodity prices.

These findings could also serve as valuable insights for future research endeavors aimed at constructing models that link real estate market dynamics to macroeconomic indicators.

Using a variety of econometric approaches, this paper presents an innovative empirical analysis of the intricate relationship between euro property prices, stock prices, gold prices and oil prices in the UK and Norway from 2005:Q1 to 2022:Q2. Expanding upon the existing literature on housing market price determinants, this study delves into the role of gold and oil prices, considering their impact on industrial production and overall economic growth. This paper provides valuable policy insights for effectively managing the impact of oil price shocks on the housing market.

This paper aims to explore the relationship between economic policy uncertainty (EPU) and promoters’ share pledging activity for real estate and construction firms in India. The author further divides the sample into financially sound and financially constrained firms and re-examines the relationship between EPU and promoters’ share pledging activity for them. Additionally, the author investigates the moderating effect of EPU on firm-level cash holding for pledged firms.

The author conducts multiple regression to examine the effect of EPU on the share-pledging activity of a firm on sample data of Indian construction and real estate firms. The financial and pledging data was collected for all listed firms from March 2009 to March 2020 from the Centre for Monitoring Indian Economy. The EPU data was re-estimated using the three-period moving average method. All data used in the study was collected from secondary sources.

The author finds that EPU influences pledging activity, and the association between them is opposite for financially constrained and financially sound firms. Also, the author reports that an increase in EPU increases firm-level cash holding for pledged firms, and the interaction between EPU and share pledging is significantly associated with firm-level cash holding.

The managerial implications of this study are manifold. Managers of financially constrained firms should pay attention to the promoters pledging activity so that in a rising EPU environment, issues of managerial entrenchment can be avoided. Moreover, any further promoters’ share pledging activity under rising EPU conditions may force managers to hoard higher cash and thus reducing investment and profitability.

This paper presents evidence of relationship between EPU, share pledging activity and firm-level cash holding in an emerging economy. The study also compares the response of financially constrained and financially sound firms for EPU on equity pledging activity and that of equity pledging on firm-level cash holdings.

The purpose of this paper is to assess the long-run and short-run drivers of real house prices in Nigeria from 1991Q1 to 2020Q4.

Vector autoregression and cointegration tests were used to assess the key drivers of Nigeria’s real house prices in the long run and short run.

The empirical findings revealed that household disposable income is the most important determinant of house prices in Nigeria. House prices increased by 1.6% and 60.8% in response to a 1% increase in disposable income in the long run and short run, respectively, while real mortgage credits pushed up house prices by 5% and have no long-run effects, suggesting that most Nigerians depend on their money income rather than credits in securing a home. In addition, prices of oil sector products and real interest rates had negative and significant relationship with house prices, while positive correlations were found for real effective exchange rate and real housing investments regardless of the time horizon. The impact of construction costs and cement prices was also documented.

This is likely a pioneering study of its kind to focus on the determinants of real house prices in Nigeria. It is probably the first study, the best of the author’s knowledge, to empirically examine the impact of the oil sector on house prices in the country.

This paper aims to propose a model for democratization of Islamic home financing to tackle the issue of sustainability of homeownership affordability.

A conceptual framework and fractional equity model (FEM) are developed to incorporate big data analytics, artificial intelligence and blockchain technology in an ecosystem for affordability and sustainability of homeownership via the proposed financing model. In addition, the FEM adopts the simulation approach to show its validity in terms of liquidity when compared with traditional home financing. In this regard, this paper is focused on developing and demonstrating the feasibility of a new financing model, rather than testing specific hypotheses or relationships. This is to propose the democratization model for Islamic Home Financing that will not benefit the prospective home buyers without compromising the profitability of the financial institutions.

The findings indicate that the proposed end-to-end solution within the financing ecosystem can lead to more efficient matching market between the buyers and sellers of houses, reduced transaction costs, greater transparency and enhanced efficiency which in the end could lead to lower costs of owning homes and sustained financial resilience among house owners. The findings indicate that the FEM model is able to increase homeownership with more elements of liquidity, marketability and sustainability for homebuyers.

This research highlights the potential of big data and blockchain technology in democratizing Islamic home financing and evidence that the transfer of ownership is possible through tokenization. However, this will require a mature financing environment to adapt the technology for practical application.

The model proposes a solution to propagate shared prosperity among stakeholders such as the house buyers/owners, sellers, investors as well the government agencies. The proposed FEM model provides alternative home financing that is more marketable, flexible and sustainable for households/buyers and financiers.

It is hoped that with the proposed financing ecosystem to promote affordability and sustainability of homeownership via big data analytics, artificial intelligence and blockchain technology can lead to greater financial resilience for homeowners which can then be translated to enhanced well-being, increased productivity and can further promote economic growth.

This research is a concept paper based on academic research and industry collaboration with a technology provider.