317 resultados para real estate investment


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While style analysis has been studied extensively in equity markets, applications of this valuable tool for measuring and benchmarking performance and risk in a real estate context are still relatively new. Most previous real estate studies on this topic have identified three investment categories (rather than styles): sectors, administrative regions and economic regions. However, the low explanatory power reveals the need to extend this analysis to other investment styles. We identify four main real estate investment styles and apply a multivariate model to randomly generated portfolios to test the significance of each style in explaining portfolio returns. Results show that significant alpha performance is significantly reduced when we account for the new investment styles, with small vs. big properties being the dominant one. Secondly, we find that the probability of obtaining alpha performance is dependent upon the actual exposure of funds to style factors. Finally we obtain that both alpha and systematic risk levels are linked to the actual characteristics of portfolios. Our overall results suggest that it would be beneficial for real estate fund managers to use these style factors to set benchmarks and to analyze portfolio returns.

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The Asian region has become a focus of attention for investors in recent years. Due to the strong economic performance of the region, the higher expected returns in the area compared with Europe and the USA and the additional diversification benefits investment in the region would offer. Nonetheless many investors have doubts about the prudence of investing in such areas. In particular it may be felt that the expected returns offered in the countries of the Asian region are not sufficient to compensate investors for the increased risks of investing in such markets. These risks can be categorised into under four headings: investment risk, currency risk, political risk, and institutional risk. This paper analyses each of these risks in turn to see if they are sufficiently large to deter real estate investment in the region in general or in a particular country.

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This study jointly examines herding, momentum trading and performance in real estate mutual funds (REMFs). We do this using trading and performance data for 159 REMFs across the period 1998–2008. In support of the view that Real Estate Investment Trust (REIT) stocks are relatively more transparent, we find that stock herding by REMFs is lower in REIT stocks than other stock. Herding behavior in our data reveals a tendency for managers to sell winners, reflective of the “disposition effect.” We find low overall levels of REMF momentum trading, but further evidence of the disposition effect when momentum trading is segregated into buy–sell dimensions. We test the robustness of our analysis using style analysis, and by reference to the level of fund dividend distribution. Our results for this are consistent with our conjecture about the role of transparency in herding, but they provide no new insights in relation to the momentum-trading dimensions of our analysis. Summarizing what are complex interrelationships, we find that neither herding nor momentum trading are demonstrably superior investment strategies for REMFs.

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The nature of private commercial real estate markets presents difficulties for monitoring market performance. Assets are heterogeneous and spatially dispersed, trading is infrequent and there is no central marketplace in which prices and cash flows of properties can be easily observed. Appraisal based indices represent one response to these issues. However, these have been criticised on a number of grounds: that they may understate volatility, lag turning points and be affected by client influence issues. Thus, this paper reports econometrically derived transaction based indices of the UK commercial real estate market using Investment Property Databank (IPD) data, comparing them with published appraisal based indices. The method is similar to that presented by Fisher, Geltner, and Pollakowski (2007) and used by Massachusett, Institute of Technology (MIT) on National Council of Real Estate Investment Fiduciaries (NCREIF) data, although it employs value rather than equal weighting. The results show stronger growth from the transaction based indices in the run up to the peak in the UK market in 2007. They also show that returns from these series are more volatile and less autocorrelated than their appraisal based counterparts, but, surprisingly, differences in turning points were not found. The conclusion then debates the applications and limitations these series have as measures of market performance.

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Purpose – The purpose of this paper is to examine individual level property returns to see whether there is evidence of persistence in performance, i.e. a greater than expected probability of well (badly) performing properties continuing to perform well (badly) in subsequent periods. Design/methodology/approach – The same methodology originally used in Young and Graff is applied, making the results directly comparable with those for the US and Australian markets. However, it uses a much larger database covering all UK commercial property data available in the Investment Property Databank (IPD) for the years 1981 to 2002 – as many as 216,758 individual property returns. Findings – While the results of this study mimic the US and Australian results of greater persistence in the extreme first and fourth quartiles, they also evidence persistence in the moderate second and third quartiles, a notable departure from previous studies. Likewise patterns across property type, location, time, and holding period are remarkably similar. Research limitations/implications – The findings suggest that performance persistence is not a feature unique to particular markets, but instead may characterize most advanced real estate investment markets. Originality/value – As well as extending previous research geographically, the paper explores possible reasons for such persistence, consideration of which leads to the conjecture that behaviors in the practice of institutional-grade commercial real estate investment management may themselves be deeply rooted and persistent, and perhaps influenced for good or ill by agency effects. - See more at: http://www.emeraldinsight.com/journals.htm?articleid=1602884&show=abstract#sthash.hc2pCmC6.dpuf

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This study investigates the determinants of cross-border capital flows into direct real estate markets. In particular, it investigates how existing institutional, regulatory and real estate specific barriers affect cross-border real estate inflows and outflows in a sample of 24 developed and emerging countries, and whether investors seek out targets with lower barriers and regulatory arbitrage. We do not find evidence of significant cross-border institutional or regulatory arbitrage in the real estate market. However, real estate market liquidity is found to be the most important driver of cross-border flows. While many of the institutional barriers included in this analysis do not appear to impact the level of real estate inflows significantly, their presence tends to suppress real estate capital outflows to other countries. Overall, easy access to financial markets, a good economic environment and transparent real estate markets may enhance real estate outflows, while returns and the macroeconomy are found to enhance domestic real estate investment.

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Trading commercial real estate involves a process of exchange that is costly and which occurs over an extended and uncertain period of time. This has consequences for the performance and risk of real estate investments. Most research on transaction times has occurred for residential rather than commercial real estate. We study the time taken to transact commercial real estate assets in the UK using a sample of 578 transactions over the period 2004 to 2013. We measure average time to transact from a buyer and seller perspective, distinguishing the search and due diligence phases of the process, and we conduct econometric analysis to explain variation in due diligence times between assets. The median time for purchase of real estate from introduction to completion was 104 days and the median time for sale from marketing to completion was 135 days. There is considerable variation around these times and results suggest that some of this variation is related to market state, type and quality of asset, and type of participants involved in the transaction. Our findings shed light on the drivers of liquidity at an individual asset level and can inform models that quantify the impact of uncertain time on market on real estate investment risk.

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Liquidity is a fundamentally important facet of investments, but there is no single measure that quantifies it perfectly. Instead, a range of measures are necessary to capture different dimensions of liquidity such as the breadth and depth of markets, the costs of transacting, the speed with which transactions can occur and the resilience of prices to trading activity. This article considers how different dimensions have been measured in financial markets and for various forms of real estate investment. The purpose of this exercise is to establish the range of liquidity measures that could be used for real estate investments before considering which measures and questions have been investigated so far. Most measures reviewed here are applicable to public real estate, but not all can be applied to private real estate assets or funds. Use of a broader range of liquidity measures could help real estate researchers tackle issues such as quantification of illiquidity premiums for the real estate asset class or different types of real estate, and how liquidity differences might be incorporated into portfolio allocation models.

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Momentum strategies have the potential to generate extra profits in private real estate markets. Tests of a variety of frequencies of portfolio reweighting identify periods of winner and loser performance. There are strong potential gains from momentum strategies that are based on prior returns over a 6- to 12-month period. Whether these gains are attainable for real-world investors depends on transaction costs, but some momentum strategies do produce net excess returns. The findings hold even if returns are unsmoothed to reflect underlying market prices.

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The linkage between corporate commitment to environmental, social and governance (ESG) issues and investment performance has generated a substantial body of research outside the real estate sector. Nevertheless, the relationship between the environmental performance and financial performance of companies is still not well understood as studies have found mixed and contradicting results. Drawing upon the KLD database which contains ratings on seven ESG dimensions from 2003-2009, this paper investigates the relationship between the ESG rating and the financial performance of a sample of US real estate firms. Since the primary transmission channel from ESG activities to financial performance may be better reflected by a firm's intangible assets, we model both Tobin's q and the total annual return in a panel framework with time and sector specific fixed effects. Our results are largely consistent with the existing literature finding a positive relationship between CFP and CSP. Further, the time scale of the lagged effects seems plausible.

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The purpose of the study is to seek a better understanding of the investment allocation behaviour of the real estate mutual funds by focusing on asset allocation at the country level. Analysing the country allocation of 553 real estate mutual funds domiciled in 20 countries, we attempt to trace how investment bias exists across countries and affects their country allocations. Our results evidence the existence of disproportionate country allocation to their domestic markets (domestic bias) and to each foreign market (foreign bias). We also find each bias is influenced by different sets of variables: real estate market influences for domestic bias and familiarity influences for foreign bias. This difference in factors influential for each bias in part explains the conflated relationship between the two biases.