898 resultados para Real estate investment
Resumo:
Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The results suggest that real estate forecasts are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that real estate forecasters display the characteristics associated with a consensus indicating herding.
Resumo:
Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. It compares the performance of real estate forecasters with non-real estate forecasters. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters and a similar survey of macro-economic and capital market forecasters, these forecasts are compared with actual performance to assess a number of forecasting issues in the UK over 1999-2004, including forecast error, bias and consensus. The results suggest that both groups are biased, less volatile compared to market returns and inefficient in that forecast errors tend to persist. The strongest finding is that forecasters display the characteristics associated with a consensus indicating herding.
Resumo:
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.
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Persistence of property returns is a topic of perennial interest to fund managers as it suggests that choosing those properties that will perform well in the future is as simple as looking at those that performed well in the past. Consequently, much effort has been expended to determine if such a rule exists in the real estate market. This paper extends earlier studies in US, Australian, and UK markets in two ways. First, this study applies the same methodology originally used in Young and Graff (1996) making the results directly comparable with those in the US and Australian property markets. Second, this study uses a much longer and larger database covering all commercial property data available from the Investment Property Databank (IPD), for the years 1981 to 2002 for as many as 216,758 individual property returns. While the performance 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 leading to the conjecture that behaviors in the practice of commercial real estate investment management are themselves deeply rooted and persistent and perhaps influenced for good or ill by agency effects
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This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.
Resumo:
Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.
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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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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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We evaluate the profitability of investments in residential property in Germany after unification with a focus on the comparison of East and West Germany. Calculations are carried out for (1) the after-tax return an investor might have expected at the beginning of the 1990s, and (2) the after-tax return that has been realized ten years after. We compare a set of statistical data for investments in fifty major cities by using complete financial budgeting. The results show that tax subsidies could not always protect investors from losing money, but they have boosted realized returns after tax considerably. Therefore, it was indeed the taxpayers, not the investors, who have borne the cost of reconstructing East Germany.