847 resultados para Commercial real estate


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The performance of real estate investment markets is difficult to monitor because the constituent assets are heterogeneous, are traded infrequently and do not trade through a central exchange in which prices can be observed. To address this, appraisal based indices have been developed that use the records of owners for whom buildings are regularly re-valued. These indices provide a practical solution to the measurement problem, but have been criticised for understating volatility and not capturing market turning points in a timely manner. This paper evaluates alternative ‘Transaction Linked Indices’ that are estimated using an extension of the hedonic method for index construction and with Investment Property Databank data. The two types of indices are compared over Q4 2001 to Q4 2012 in order to examine whether movements in these indices are consistent. The Transaction Linked Indices show stronger growth and sharper declines than their appraisal based counterparts over the course of the cycle in different European markets and they are typically two to four times more volatile. However, they have some limitations; for instance, only country level indicators can be published in many cases owing to low trading volumes in the period studied.

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This paper examines the impact of changes in the composition of real estate stock indices, considering companies both joining and leaving the indices. Stocks that are newly included not only see a short-term increase in their share price, but trading volumes increase in a permanent fashion following the event. This highlights the importance of indices in not only a benchmarking context but also in enhancing investor awareness and aiding liquidity. By contrast, as anticipated, the share prices of firms removed from indices fall around the time of the index change. The fact that the changes in share prices, either upwards for index inclusions or downwards for deletions, are generally not reversed, would indicate that the movements are not purely due to price pressure, but rather are more consistent with the information content hypothesis. There is no evidence, however, that index changes significantly affect the volatility of price changes or their operating performances as measured by their earnings per share.

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An appraisal task involves the rendering of market value, an unobservable and hypothetical construct. Direct feedback against this objective is typically not possible, so alternative feedback such as confirmation of previous appraised values may be employed. This may alter the appraiser’s perception of the valuation objective leading to divergence from the appraisal normative model. The real estate literature suggests appraisers have been susceptible to the influence of previous appraised values, often resulting in biased valuations. This research focuses on the efficacy of a decision support tool in eliminating or subduing this bias in the appraisal process.

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In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naïve and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.

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The paper analyses the evolving corporate real estate supply chain and the interaction of this evolution with emerging business models in the serviced office sector. An enhanced model of the corporate real estate portfolio is first presented incorporating vacant, alienated and transitory space. It is argued that the serviced office sector has evolved in response to an increasingly diverse corporate real estate portfolio. For the peripheral corporate real estate portfolio, the core serviced workspace product provides the ability to rapidly acquire high-quality workspace and associated support services on very flexible bases. Whilst it is arguably a beta product, the core workspace offer is now being augmented by managed office or back-to-back leases which enables clients to complement the advantages of serviced offices with a wider choice of premises. Joint venture business models are aligned with solutions to problems of vacant space.

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This paper examines the predictability of real estate asset returns using a number of time series techniques. A vector autoregressive model, which incorporates financial spreads, is able to improve upon the out of sample forecasting performance of univariate time series models at a short forecasting horizon. However, as the forecasting horizon increases, the explanatory power of such models is reduced, so that returns on real estate assets are best forecast using the long term mean of the series. In the case of indirect property returns, such short-term forecasts can be turned into a trading rule that can generate excess returns over a buy-and-hold strategy gross of transactions costs, although none of the trading rules developed could cover the associated transactions costs. It is therefore concluded that such forecastability is entirely consistent with stock market efficiency.

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Customer Relationship Management (CRM) theory suggests that good customer service results in satisfied customers, who in turn are more likely to remain loyal and recommend the service provider to others. Applied to real estate, this theory implies that landlords should see a return on any investment in the service they give to tenants, in the form of increased lease renewal rates and fewer void periods, achieved without compromising rents. This paper examines determinants of occupier satisfaction, and investigates the relationship between occupier satisfaction and property performance, using measures such as capital growth, income return, lease renewal rates and total return. The analysis is based upon a pilot study using occupier satisfaction responses from around 2500 interviewees based in multi-tenanted offices, shopping centres and retail warehouses on out-of-town retail parks in the UK. The analysis is being extended to cover a larger sample for the author’s PhD. Part 1 of the analysis examines occupier satisfaction, whilst Part 2 considers its impact on property performance.

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We compare and contrast the accuracy and uncertainty in forecasts of rents with those for a variety of macroeconomic series. The results show that in general forecasters tend to be marginally more accurate in the case of macro-economic series than with rents. In common across all of the series, forecasts tend to be smoothed with forecasters under-estimating performance during economic booms, and vice-versa in recessions We find that property forecasts are affected by economic uncertainty, as measured by disagreement across the macro-forecasters. Increased uncertainty leads to increased dispersion in the rental forecasts and a reduction in forecast accuracy.

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This study examines the rationality and momentum in forecasts for rental, capital value and total returns for the real estate investment market in the United Kingdom. In order to investigate if forecasters are affected by the general economic conditions present at the time of forecast we incorporate into the analysis Gross Domestic Product(GDP) and the Default Spread (DS). The empirical findings show high levels of momentum in the forecasts, with highly persistent forecast errors. The results also indicate that forecasters are affected by adverse conditions. This is consistent with the finding that they tend to exhibit greater forecast error when the property market is underperforming and vice-versa.

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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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We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers' as well as institutional investors' perspectives.