Real Estate Returns Research Articles

The Influence Factors on Stock Returns of Real Estate and Property Companies Listed in Bei in 2010 - 2014

This research seeks to examine and offer insights into the factors that impact stock returns of real estate and property companies listed on the Indonesia Stock Exchange. The examined factors include DER, EPS, NPM, PBV, inflation, exchange rate, SBI, and GDP. The research focuses on real estate and property companies listed on the Indonesia Stock Exchange during the 2010-2014 period, involving a total of 38 companies. The study analyzes the impact of these variables DER, EPS, NPM, PBV, inflation, exchange rate, SBI, and GDP on the stock returns of these companies. Data were collected from sources such as Bank Indonesia, the Central Bureau of Statistics, and the Indonesia Stock Exchange. The findings reveal that DER, EPS, NPM, and PBV significantly influence stock returns, whereas inflation, exchange rate, SBI, and GDP do not have a significant impact on the stock returns of real estate and property companies.

Interconnectedness between real estate returns and sustainable investments: A cross-quantilogram and quantile coherency approach

The real estate sector is a substantial energy consumer, contributing to a large share of global greenhouse gas emissions. Despite the known links between the real estate sector and sustainable assets, studies exploring co-movements or dependence between them are still scarce. The present paper contributes to this challenging problem by capturing and analyzing the non-linear dependence over time and frequency between real estate returns and sustainable assets - green bonds, clean energy and environmental, social, and governance (ESG) stocks. We adopt a modeling approach that utilizes both the cross-quantilogram and the quantile coherency method. Our empirical results indicate unidirectional dependence from the real estate sector to most sustainable assets in both tails and under normal market conditions, although bidirectional dependence in the lower quantiles. Moreover, based on recursive window estimations, when the Covid-19 period is included, green bond and real estate returns are tail-dependent both during boom and bust periods. However, in non-pandemic periods, higher dependency is found during booms. Furthermore, the returns of the green bonds are less dependent on real estate returns compared to other sustainable assets. Our findings are potentially relevant for investment portfolio and public policy decision-making.

Do Real Estate Investments Yield the Highest Returns in Pakistan?

The investment choices of economic agents are critical in determining the value of capital stock in different sectors of the economy. These choices depend upon the available investment options in society and the expected rate of returns. In the case of Pakistan, it is commonly perceived that real estate investment in the form of buying a piece of land or buying a house comparatively yields the highest returns. This study aims to devolve on this presumption and estimate returns from different available investment avenues. Our findings, contrary to common perception, suggest investment in stocks yields the highest real returns while real estate returns stand second. However, the associated risk with stock investment is higher than in the real estate sector. Therefore, one can argue that real estate investment offers better returns comparatively. Surprisingly, we also find that the real returns from treasury bills, national savings accounts, and silver are negative. We also delve into the potential determinants of real estate returns and their impact on investment outcomes. The estimation results reveal that GDP growth, interest rate, and inflation pandemic are significantly affecting the rate of returns from real estate, while the Covid pandemic has negatively affected the returns from housing.

Market perceptions of distress and its impact on returns: evidence from the U.S. commercial real estate market

ABSTRACT This paper examines the relationship between market participants’ sentiment regarding distress in the real estate market, captured through internet search queries, and the U.S. commercial real estate market. We use Google search frequency to construct a measure of market perception of distress, the Market Distress Perception Index (MDP Index), and determine the extent to which this index can help predict future private commercial real estate returns in the U.S. The results show that our pessimistic sentiment index predicts returns of commercial real estate up to three quarters in advance. These results hold at the national, regional, and state levels and are robust across various model specifications. The predictability of the sentiment index is especially pronounced during recessionary periods. We also analyse different property sectors and find that the inverse relationship between the MDP Index and future private commercial real estate returns persists across all sectors except the industrial sector. The relationship is strongest for the office sector.

Public real estate returns and inflation shocks: The central role of inflation nonneutrality

AbstractWe study the comovement of public real estate returns and inflation shocks over 1981–2022, using both survey‐based expected inflation and the Consumer Price Index (CPI). We find a complex relation that is: strongly negative during weaker‐economic (WE) times over the 1980s and 1990s, when stagflation was more a concern; strongly positive during WE times over roughly 2000–2022, when low growth with low inflation tended to be more a concern; and marginally negative otherwise. Linking inflation to both macroeconomic fundamentals and real estate operational data, we show that inflation shocks comove with changing beliefs about the underlying economic‐growth state and/or the risk premium. Thus, we argue that inflation nonneutrality has a central role in understanding our findings.

Importance of the innovation term for GARCH modelling of direct real estate returns

ABSTRACT The autoregressive heteroscedastic effects of the conditional volatility processes of direct real estate (capital value) returns are subject to a broad range of econometrics. However, while many specifications have been utilised in the empirical design, the literature has commonly modelled the innovation term within the GARCH volatility processes of real estate capital values through a Gaussian normal distribution. This a priori assumption falls short of the data characteristics exhibited by capital value returns, implying that capital value returns cannot be adequately modelled without adapting to the innovation term distribution. Misspecification can underestimate risk and lead to the over-allocation of riskier assets. This study investigates the impact of the a priori assumption about the innovation terms applied to capital value returns, as well as their robustness, through a time-varying framework. The main findings are that misspecification and parameterisation occur when assuming the normality of the innovation term, and that the application of a priori assumptions of the innovation term beyond those of a normal, Student’s t, or generalised error distribution currently employed in the literature can increase the validity of volatility models when applied to capital value returns. The application of the Johnson – SU distribution yields the best overall performance.

The Impact of Inflation on Real Estate Investment Perfomance And Effective Investment Decisions

Purpose: This study aims to examine the impact of inflation on key variables of real estate investment performance and investment decisions. Theoretical Reference: This paper considers several models of real estate investment performance indicators because the effect of inflation on key variables of real estate investment performance is an important factor in investment decisions. Since effective investment decision is key to avert investment loss especially during inflation period, this paper follows the suggestions by Otegbulu (2022) and Georgiv, et al (2002) that property incomes and values are not static during periods of inflation bur responds to economic dynamics, and could infact trigger favourable investment opportunities in real estate. This paper therefore follows these models/suggestions of Otegbulu (2022) and Geoargiv, et al, (2002) to examine several real estate investment to offer appropriate reflection of how inflation impacts of incomes from real estate investment. Method: Data collected were analysed using Pearson Correlation Analysis to determine the relationship between inflation rate and real estate investment performance (measured by annual returns). Regression analysis was also employed on the data to determine the level of contribution or degree of impact of inflation on real estate performance. Also data collected on the exchange rate and real estate performance over the study period were analysed using Pearson Correlation Analysis to determine the relationship between exchange rate and real estate investment performance (measured by annual returns on investment). Regression analysis was also employed on the data to determine the degree of impact of exchange rate on real estate investment performance. Data collected for the analysis and hypotheses testing were secondary data over a period from 2005 – 2022. Result: The study reveals that real estate investment market generates average total annual returns of 21.39% under average inflation rate of 12.5%. The test statistics (Pearson Correlation) results shows that the higher the inflation rate, the lower the performance of the real estate investment. Also, the study reveals that as inflation persists causing exchange rate fluctuations, the test statistics (Pearson Correlation) results shows that higher exchange rate causes lower performance of real estate investment. This could be because more than 90% of the real estate construction materials in the study are imported. Conclusion: It is clear and obvious that inflation impacts highly on real estate and capable of distorting projections in property investment. Rational investors must therefore factor in inflation risk in investment decisions. The study has shown that inflation has significant impact on annual returns of real estate and consequently affects investment performance. The study concluded that the higher the inflation, the lower the performance of the real estate investment and that the continuous rise in inflation rate reduces the purchasing power of the local currency leading to local currency devaluation. Also, it was concluded that higher exchange rate causes lower performance of the real estate in terms of annual returns. Research Implications: One of the major implications of the findings from this study is that as inflation raises the volatility of local currency which adversely affect the cost of construction, real estate investment performance is hindered. The risk element increases which could lead to project cost over-run, abandonment or increased vacancy rate. Investors become skeptical in making investment decisions because of uncertainties. Policy makers should put in place policies and guidelines that will attract cross-border investors who can take advantage of the local currency devaluation to improve their real estate investment portfolios. Originality/Value: The relationship between inflation rate, exchange rate and real estate performance (measured by rate of returns on the investment) is of great concern for real estate practitioners and investors. The study is original well thought efforts of the authors as contribution to real estate practice and education in developing economies currently being threatened by rising inflation. It is believed that this study will be very useful to global investors who will like to invest in the study area in particular and other emerging markets in general.

Investable Real Estate Allocations in a Mixed Asset Portfolio; Both Long Term and During Different Cycles

The NCREIF Property Index (NPI) data starts in 1978 and has been used as a benchmark index for over 45 years. In 2006 NCREIF created the NCREIF Open-End Diversified Core Equity Index (ODCE) and used historic fund level data to create performance data back to 1978. ODCE was the first “investable index ” in direct real estate for institutional investors, family offices, and high net worth investors who can meet these direct funds’ minimum investment levels (typically $5 million). Individual investors with less money can also access ODCE returns through Interval Funds or “Fund-of-Funds” that invest in and are designed to track or beat the ODCE Index. Since 2009 general partners of funds are required to update their net asset value (NAV) to “fair market value” on a quarterly basis as a result of Topic 820 of the Financial Accounting Standards Board. Both ODCE funds and interval funds have improved their liquidity with either monthly or quarterly redemption options, making them more competitive (from a liquidity aspect) with publicly traded securities. We analyze portfolio allocations over 45 years – the longest time frame ever studied and over 6 NEBR economic cycles and 4 ODCE real estate return cycles using Markowitz efficient frontier analysis. We inspect up-cycle and down-cycle periods separately and add to the literature by analyzing the ¼, ½, and ¾ points (low, medium, and high risk/return points) along the Markowitz efficient frontier. Our findings support many of the 45 studies published, but conflict with some depending upon their study methodology and time frame (9 to 25 years) studied. We conclude that real estate would have improved historic risk adjusted returns in many cycle periods.

Real Estate Return Distributions with New NCREIF Data Series

The accuracy of real estate return distribution parameter estimation is affected by the tools used to do the work as well as the data sets employed. Consistent with previous studies, investment risk models with infinite variance describe distributions of individual property returns in the new NCREIF Indicators: Capital Performance and Property Operations individual property database over the period 1990–2021. Applying Maximum Likelihood Estimation (MLE) to historic data shows real estate investment risk to be heteroscedastic, but the Characteristic Exponent of the investment risk function varies more among property types than previously reported whether computed by MLE or other estimation techniques.

Investment Factors and Decision Behavior Affecting to Real Estate Investment Decision

This study examines industry's significance to a nation's economic development and to the expansion of its many stakeholders cannot be overstated. Out of all the sector's stakeholders, the investor is the one who takes on the most risk. When it comes to an investor's propensity to invest in the actual market, certain elements have the biggest impact on their motivation and behaviour, while others have the least. Real estate returns vary depending on the area. This is supporting the expanding field of Real Estate research. The behavioural factor like over confidence, education, and religion was examined, and it was discovered that religious factors impact Indian investors' decisions to invest in real estate. This is advancing the field of research in the real estate industry. The goal of this investigation is to discover the tactics exploited by Indian developers to optimize monetary benefit from multiple real estate investments. A critical element to take into account when making investments in Indian property investment is the financial side. The way of decision for investment are dependent on various variable that differ from case to case, nature of the area, financial capability of investor, risk and policies, which make the behaviour of real estate dynamic through uncertainty and volatility. This makes the decision making for all the investors in real estate difficult. Various investment models present in real estate investment decision making are identified and compared in terms of variable associated, cater to level of risk, assumption, type of decision, metrics and investment types. This research International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 07 Issue: 03 | March - 2023 Impact Factor: 7.185 ISSN: 2582-3930 © 2023, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM18222 | Page 2 will serve as a guide to investors, developers and builders. It will provide a prior knowledge to take a decision on investment in commercial properties of offices and retail. Keywords: Financial Study, Real Estate, Investor’s Decision, Real Estate Investment, Real Estate Investment Factor, Real Estate Sector.

The Relationship Between Geopolitical Risks and Housing Returns in Türkiye: Evidence from the Cross - Quantilogram

The aim of the study is to analyze whether geopolitical risks have an effect on housing returns in Türkiye based on the data for the period January 2010 – September 2021. Considering its geography, Türkiye is one of the countries most likely to be exposed to geopolitical risks in the world. For this reason, from the point of view of both domestic and foreign investors investing in housing market, it is important to know whether this situation affects real estate returns, especially in periods when the growth in geopolitical risks is high and very high. For this purpose, in this study, the Cross-Quantilogram method introduced in the paper of Han et al.(2016), which is a robust measure of quantile dependence of two variables, was used. As a result of the analysis, it is seen that median and high-level geopolitical risks do not have an effect on housing prices or housing returns, but very high geopolitical risks have a short-term negative effect on returns. Based on all the findings, it is concluded that the geopolitical risks in Türkiye do not have a significant and permanent effect on the housing market.

Real Estate Exposures to Bond and Equity Return Drivers

Real Estate Exposures to Bond and Equity Return Drivers

Household willingness to take financial risk: Stockmarket movements and life‐cycle effects

Using panel data on Australian households, the relationship between risk tolerance and past stock returns is investigated across economic and financial cycles, as well as over the life-cycle and across generations. Risk tolerance is found to be procyclical with stock returns over an eight year horizon. The empirical results also reveal an inverted J-curve age risk profile, and the presence of a longer cycle across generations. Results are robust to controlling for financial crises, return volatility, real estate returns and home bias.

Sovereign public sector property fund: Building a conceptual framework

The public sector is the largest UK landowner and space occupier with local authorities owning and managing the majority of the real estate assets to meet services to the community. As central funding of these services reduce and the knowledge economy is changing the way we live, local governments are looking at more efficient and effective ways of managing their real estate operations and creating investment value to bridge the gap between funding shortfalls and the demand for public services. Several local authorities are now investing in commercial properties as a way to generate long term stable income streams although current practices are highlighting narrow portfolio diversification, management challenges, fee leakage and limited awareness of the knowledge economy on future real estate returns. This research paper examines the issues and provides a conceptual framework for a Sovereign Public Sector Property Fund which can create local level opportunities alongside a stable long term income stream. This can be achieved through a pooling of prime local government real estate assets to offer portfolio diversification with quality management, good governance, local authority appointed steering committee members and exposure to opportunities to benefit from aspects of the knowledge economy. Supported by central government, individual real estate assets in a Sovereign Public Sector Property Fund can provide a local destination with placemaking potential in the post COVID-19 era. Strengthening the connection between people and place, the real estate in the fund can be the catalyst for local employment opportunities and support surrounding communities. This exploratory study covers an important part of the UK economy and offers a valuable insight into creating a new real estate investment vehicle which can elevate the often underutilised prime local authority real estate assets.

High-order Gaussian RBF-FD methods for real estate index derivatives with stochastic volatility

The 2008 financial crisis showed the necessity for managing risk associated with the price movements of real estate assets. Appropriate financial instruments for hedging real estate portfolios include options on a real estate index. Based on empirical evidence that real estate returns exhibit time varying volatility, a real estate index derivative pricing model with stochastic volatility is proposed. An efficient procedure using Gaussian radial basis functions-finite differences is developed for the numerical solution of the two-dimensional pricing partial differential equation. Fourth-order convergence rates on uniform meshes for European options are numerically demonstrated and the algorithm is also shown to compute accurate American option prices. A numerical study of the stability of the scheme reveals that errors remain small.

Commercial Real Estate Returns and Innovation

We investigate the relation between commercial real estate (CRE) returns and regional innovativeness and find that regions with more innovation exhibit higher total returns on commercial property. And, when we investigate the extent to which income return and capital return on commercial properties are related to local innovativeness, we report a positive relation between innovativeness and income return but little to no association between innovativeness and capital return. Our paper also provides some initial evidence suggesting that local innovativeness is related to better future CRE performance. Overall, this paper suggests that the innovativeness of a region is economically and statistically positively related to CRE returns, adding to a budding literature investigating CRE returns and extensive literature researching innovation.

Macroeconomic risk factors and Chinese FDIs in real estate: evidence from the Asia-Pacific public real estate markets

PurposeThe aim of this study is to shed light on the relative importance of Chinese (Mainland China and Hong Kong: CH-HK) foreign direct investments (FDIs) in real estate (FDIRE) on the dynamics of Asia-Pacific (APAC) public real estate markets after the Global Financial Crisis.Design/methodology/approachUsing a parsimonious real estate asset-pricing model including macroeconomic risk factors, the authors develop a metric to measure FDIs in the real estate sector. The authors use a panel VAR approach based on robust econometric methodology (generalized method of moments) and deal with potential endogeneity and an eventual causality problem. The authors also compute multiple metrics to measure the Chinese, US and Japanese FDIs in the real estate sector.FindingsThe study results report a positive significant impact of CH-HK FDIRE on APAC public real estate returns, while FDIRE originating from outside China are not significant. The authors also show that Chinese investors use the channel of FDIs in Diversified Listed Property Companies (LPCs) and Hotel and Family LPCs to gain exposure to the APAC real estate markets. The study results suggest that APAC property markets are mainly impacted and emphasize the importance of an intercontinental diversification strategy for investors in LPCs in the APAC region.Practical implicationsContrary to Bond et al. (2003) who identified that APAC public real estate markets were overwhelmingly idiosyncratic in the decade preceding China's WTO membership (1990–2001), the study findings underline that Chinese FDIRE became a common factor affecting all eight markets in this study in the decade following the global financial crisis (2007–2017). The results emphasize the importance of an intercontinental diversification strategy for investors in LPCs in the APAC region.Originality/valueThe authors use a parsimonious model, introduce metrics to measure FDIRE and apply a panel VAR approach based on a robust econometric methodology to shed light on China's economic globalization strategy on Asia-Pacific public real estate markets after the GFC. The study results highlighting the major impact of CH-HK FDIRE on securitized real estate market returns dynamics, identify the existence of an Asian common factor driven by Chinese FDI inflows into neighbouring countries.

An Extended Fama-French Multi-Factor Model in Direct Real Estate Investing

Understanding risk-adjusted returns in real estate investment are crucial, but little is known about the risk-adjusted returns for direct real estate. This paper examines risk-adjusted total returns by developing an extended capital asset pricing model (CAPM) to investigate whether direct real estate returns compensate for their risk levels. Based on a panel dataset of the residential property transaction in 62 Territorial Authorities of New Zealand from 2002Q1 to 2018Q4, a direct real estate portfolio performance in the single-factor CAPM model is compared with the national housing markets stock markets and REITs markets in New Zealand before the pandemic. The results demonstrate that the direct real estate returns outperform the market returns with a significant positive alpha and beta smaller than one but positive. The alpha is further evaluated by the five-factor CAPM model, which includes the factors of liquidity risk, value risk, time risk, credit-rating risk, and currency risk. The assessment shows that most of the excess return (alpha) can be attributed to direct real estate market risks.

Sustainability and Private Equity Real Estate Returns

Sustainability and Private Equity Real Estate Returns

Uncertainty and commercial real estate excess returns in European markets

ABSTRACT We examine the link between uncertainty and the excess returns of direct commercial real estate markets using the well-established economic policy uncertainty index (EPU) and a novel measure of uncertainty, the world uncertainty index (WUI). Using a panel dataset of 17 European markets, we find a strong positive relation between the two uncertainty measures and excess returns in our univariate models and when we add real estate control variables. However, once macroeconomic control variables are included, only the WUI remains significant. We relate this finding to the more country-specific nature of the WUI, while the EPU potentially gives more weight to global news.