Chapter 6 - Uncertainty: Risk in real estate

The continued growth of the equity REIT market depends critically on investors' belief that the stock market provides fair and accurate valuations of real estate. An index of real estate stocks traded on the New York and American stock exchanges reflects changes in real estate market fundamentals in a more timely fashion than a widely used appraisal-based system. The index includes equity real estate investment trusts (REITs), real estate operating companies not organized in trust form, land subdividers and commercial developers, and general contractors. A statistical examination of the relation between the stock-based and appraisal-based series finds that the lagged returns of the real estate stocks help explain the behavior of the current-period appraisal series. The stock market apparently impounds information about changes in real estate values in a more timely manner than appraisal-based series constrained by infrequent property appraisals. oth practitioners and academics have become increasingly interested in the risks and returns of real estate ownership. In the absence of a centralized exchange to record sales, appraisal-based data such as the Russell-NCREIF Property Index (RNPI) are often used to analyze real estate returns. Such appraisal-based series are imperfect proxies for actual market conditions, however, largely because property valuations occur infrequently (quarterly at best), so appraisal-based series contain stale prices.1 This shortcoming has been highlighted recently by the failure of appraisal-based return indexes to capture either the timing or the magnitude of the recent dramatic downturn in commercial real estate markets. This article presents and analyzes the return behavior of a stock-market-based index of real estate performance. The index is composed of real-estate-related equities traded on the New York and American stock exchanges (NYSE and Amex). The firms in the index include owner-operators of existing properties as well as developers. Previous real estate research has primarily examined the returns of equity real estate investment trusts (REITs). That work generated two findings of particular relevance to this article. First, there is no significant contemporaneous correlation between equity REIT and appraisal series returns. Second, equity REIT returns are significantly positively correlated with broader stock market returns such as the SP real estate stock prices more accurately captured the industry downturn in the late 1980s than the well-known RNPI series. Despite the lack of a contemporaneous relation between appraisal and stock series, we conclude that there is an important connection between the two. This conclusion is based on a statistically and economically significant relation between lagged real estate stock returns and current-period returns on the appraisalbased RNPI. The evidence indicates that the two series incorporate similar information about real estate fundamentals, but the stock-based index does so in a more timely manner.

Market Risk of Real Estate

Purpose– The purpose of this paper is to present a practice briefing in the form of a user’s manual for Excel-based simulation of real estate risk. Based on a generic discounted cash flow model, the simulation incorporates the often ignored heavy tail behaviour of real estate investments, and consolidates Jensen’s inequality. The briefing attempts to explain a model that permits the user to decide whether to include extreme events in real estate risk modelling and how extreme these events may be. Practitioners can generate a variety of modelling outcomes and then choose risk comfort zones in which to contemplate a range of returns.Design/methodology/approach– The paper provides an overview of the underlying mathematical concepts and challenges, as well as on the perspectives on their application from the current academic literature. It offers a step-by-step walk-through of the Excel model (the model being downloadable at:www.mathestate.com).Findings– Existing models for real estate risk modelling fall short with respect to realistic simulation of the probability of extreme events due to challenges in the implementation of stable laws. These former barriers to the implementation of stable laws have been overcome by providing a unique combination of Excel-resident functionalities with a stable pseudo random number generator.Research limitations/implications– Investment advisers no longer need expensive add-ins to estimate risk. The presented Excel model is more robust than common approaches as it considers distribution shapes that are not otherwise easily available. The only apparent limitation is that users need to be familiar with the most basic functionality of Excel.Practical implications– Practitioners are provided with an easy-to-use Excel model that does not require further software add-ins. The model simulates real estate investment returns, based on a more realistic inclusion of risk behaviour. It allows specifying how much extreme value behaviour characterizes the volatility in future projections modelled to guide investment decisions.Social implications– Risk is a cost to society. Many recent news events demonstrate the importance of including extreme values in modelling. The paper attempts to contribute to more realistic risk estimation in real estate investment.Originality/value– This briefing introduces a real estate risk simulation model that includes using stable laws, using Excel, a familiar and widely used platform. Such a model has not previously been reported in the academic or practitioners’ literature.

Contemporaneous correlation between the returns of direct and indirect real estate investments is generally found to be weak. However, direct and securitized real estate returns are expected to be cointegrated over the long run, since securitized real estate returns are derived from direct real estate assets. Cointegration between direct and indirect return indices implies that the correlation between the returns converges to one as the investment horizon increases. The relative inefficiency of the direct real estate market suggests that securitized real estate prices react faster to shocks in the fundamentals than direct real estate prices. As such, securitized real estate returns are conceived as a leading indicator of direct real estate returns. Nevertheless, the opposite may also hold due to the speculative, nonfundamental related noise embedded in securitized real estate prices in the short run. This paper examines the dynamic relation between direct and indirect real estate returns in the U.S. for the period 1977Q42008Q2. It contributes to the literature by depicting the linkages between direct and indirect real estate returns, as well as by identifying the response speeds and magnitudes of direct and indirect real estate returns to shocks in the market fundamentals. The response speeds are estimated with vector error correction models.

Executive Summary. Real estate accounts for a significant proportion of the corporate assets of publicly listed companies. The real estate exposure of publicly traded companies in land scare economies such as Hong Kong and Singapore is particularly high. This study explores the real estate exposure of listed companies in Singapore where non-real estate companies are classified by their real estate asset intensity. A six-factor Arbitrage Pricing Theory (APT) model, capturing changes in real estate prices, industrial production, expected inflation, unanticipated inflation, risk premium and term structure, shows that real estate exposure is priced. In addition, the real estate risk premium is found to vary across companies with different real estate asset intensity. A close linkage is also established between real estate exposure and various industries. Other than the real estate-intensive industries such as real estate, hotel and construction, conglomerates and financial companies also have a high exposure to real estate. Interestingly, our analysis shows that real estate exposure, which is computationally tedious to determine, can be proxied by real estate asset intensity, a simple accounting measure. The implications for portfolio management in a land-scare market are examined.

Bank Risk Factors and Changing Risk Exposures of Banks: Capital Market Evidence Before and During the Financial Crisis

A restricted portfolio is constructed which includes NYSE common stocks, corporate bonds, government bonds, small capitalization common stocks, residential real estate and farmland and returns for each of four different tax brackets (0%, 15%, 30%, 45%). Next, three alternative measures of rates of return for residential real estate and farmland are used. Finally, since some researchers believe that standard risk measures (variance and standard deviation) do not capture the total risk in real estate, the risk for the real estate returns is increased five times while the returns are held constant. The twenty–four optimal portfolios (four tax brackets with two measures of risk and three measure of return for residential real estate and farmland) are then derived. These results are then compared and contrasted to each other to ascertain the change in sensitivity of the optimal portfolios due to different tax rates, different rates–of–return estimates and different risk estimates.

Building for a better hospital. Value-adding management & design of healthcare real estate

PurposeThis study aims to empirically examine the relationship between real estate and stock market of Pakistan.Design/methodology/approachThe data of two real estate indices (house price index and plot price index) are taken for the Pakistan and its four big cities, i.e. Lahore, Karachi, Rawalpindi and Islamabad. It estimates the integration between series by applying the Johansen cointegration test. Moreover, the vector error correction model is applied to examine the short and long-run causal relationships between series.FindingsThe findings show that the real estate markets are cointegrated with the stock market. They imply that the real estate and stock markets are good substitutes in investment allocation, but investors cannot get the benefit of diversification by making a portfolio of real estate and stock markets in Pakistan. Moreover, the long-run causality is observed from majority house markets to the stock market, whereas short-run causality is evident from majority plot markets to the stock market. Hence, the real estate market leads the stock market in the short run and long run, suggesting the credit-price effect in the majority of real estate markets in Pakistan. These causality results are helpful for investors in the forecasting of real estate and stock markets in Pakistan.Research limitations/implicationsThe limitation of the study is the lower number of observations (107), because house and land prices are only available in monthly frequency from January 2011 in Pakistan.Originality/valueTo the best of the authors’ knowledge, no researcher has investigated the real estate and stock market nexus in Pakistan. Therefore, this study focuses on examining the relationship between the real estate and stock market of Pakistan. The link between real estate and stock markets will provide useful insights to the portfolio managers, real estate companies, property agents, stockbrokers and investors.

Consisting of three essays, the dissertation is motivated by some existing gaps in the financial real estate literature. First, we exploit the fact that no research has used the well documented hybrid nature of real estate securities to forecast its returns. Second, we propose the first 'true' comparison of the predictability of securitized real estate and stock returns, as we argue that the previous comparisons done in the literature are biased. Third, we examine the long-run dynamics that govern the relationships between securitized real estate and the three models most commonly used to explain and forecast its returns. Our main findings suggest that the hybrid nature of real estate securities can be used to predict its returns, that securitized real estate returns are more predictable than stock returns in countries with well established REIT regimes, and that securitized real estate is fractionally cointegrated with both macroeconomic variables and the hybrid factors.

Spatial decision support systems for effective ex-ante risk evaluation: An innovative model for improving the real estate redevelopment processes

This paper is an exploratory study into the performance effects of corporate real estate (CRE) ownership for retail companies in the US. In the recent years, many brick-and-mortar retail stores have announced massive closings (as announced in 2018, 142 Sears locations will be closed, while Toys “R” Us filed for bankruptcy and announced shutting down all 800 locations). These struggles, along with the rise of e-commerce, signal significant changes in the CRE strategies for retail firms going forward. According to Gibson and Barkham (2001), CRE is closely linked to the business strategy of companies in the retail sector. As retail companies seek to assemble valuable CRE portfolios that can generate sustainable competitive advantages, inferior or inefficient locations can significantly undermine their long-term financial performance. On one hand, portfolio theory suggests that if real estate assets have a different risk profile than that of the operating business, then CRE ownership has the potential to provide diversification benefit to firms with high levels of property holdings. On the other hand, Tuzel (2010) has asserted that real estate risk is systematic, and CRE investment is riskier than investment in other types of capital for the firm due to slow depreciation of real estate. Therefore, firms with high real estate holdings are hurt more during recessions (Tuzel, 2010). For these reasons, CRE ownership has the potential to significantly impact the performance of retail companies.

Climate change exacerbates flood hazards, resulting in risks to real estate values that should be considered by long-term investors. Flood risk presents two major financial risks: market risk and credit risk. Market risk refers to potential property value loss, and credit risk increases the likelihood of mortgage defaults. However, methods and comprehensive data for quantifying global real estate flood risks are lacking. To address this problem, this paper proposes two flood risk assessment frameworks: the local-oriented approach (LOA) and global-oriented approach (GOA). Two hazard and three vulnerability assessment methods are also introduced to support these frameworks. The LOA vulnerability estimates of regions with complete records are required to support the GOA. Taiwan was selected as an example for the LOA assessment, and the results were used to estimate vulnerability overseas in GOA assessments. The results of case studies for buildings located in four cities in different countries were compared. The proposed framework enables investors and asset owners to globally quantify climate risks in real estate, even when the available data are incomplete. Users can choose the most appropriate approach on the basis of the available data and their tolerance for uncertainty.

The researcher combines his personal case study with a literature review to present his real estate investment model, exploring commercial and residential real estate investment opportunities and risks in the current market economy. The main premise of the model is that using financial acumen and systems models as the approach to investing in real estate provides the opportunity for high rates of return due to a variety of innate factors. The model explores the risks and opportunities of investing by: a) The use of leverage in property acquisitions; b) Accessing significant IRS tax advantages for investors, including the use of depreciation schedules, cost segregation models, 1031 tax-deferred exchanges, and tax-free cash-out refinancing. Risks in residential and commercial real estate can result from internal factors within the owner’s control or be caused by external factors beyond the investor’s control. AI, machine learning, and dynamic factor models for real estate investment are explored.

Although it is well known that there are many sources of risks in real estate investments, particularly in commercial real estate investments, the works are frequently commenced without consideration of risk resources and uncertainties in the project evaluation and investment decision making processes. The nature and impact on investment value of environmental, economic, real estate sector, and project risks are observed to vary from the beginning of the project development process until the end of it. Dynamic methods are often used in commonplace feasibility studies and integration of risks to calculations and periodically updating feasibility analyses are found to be usually neglected. However, project-specific risks such as the ownership of land, land development rights, and demands of the owners of neighboring parcels and economic risks directly affect the feasibility of the investment and can be major sources of failure.In this study, risk perceptions of upper middle managers of large-scale real estate development companies were evaluated and risk management approaches implemented within the companies were discussed. The scope of the study was limited to companies that are members of the Turkish Contractors Association (TCA), to which only the biggest real estate firms of Turkey can be members, and members of other important associations. In the construction and real estate market, two of the most important sectors in the Turkish economy, members of the TCA realize 70%of construction works within the country and 90%of the works undertaken by Turkish contractors abroad and have the ability to represent the industry. In this study, the impact of risk according to its resources on the preparation and implementation of real estate projects and risk perceptions of managers were examined based on the responses received to the questions electronically sent to the members of the TCA and other important associations. The study results revealed that that developers carry out risk management and decision support system activities, use intuitive risk analysis methods, utilize risks in integrated decision-making processes and the risk items that the developers consider are identified. According to the study results, sales forecasts, and the changes in foreign exchange and interest rates are significant in risk management in line with academic studies.