427 resultados para Real estate investment fund


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Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. Uncertainty in the comparable information available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the output figure, the valuation, can be conveyed to the use of the valuation, but as yet no definitive view has been taken apart from a single Guidance Note (GN5, RICS 2003) stressing the importance of recognising uncertainty in valuation but not proffering any particular solution. One of the major problems is that Valuation models (in the UK) are based upon comparable information and rely upon single inputs. They are not probability based, yet uncertainty is probability driven. In this paper, we discuss the issues underlying uncertainty in valuations and suggest a probability-based model (using Crystal Ball) to address the shortcomings of the current model.

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Uncertainty affects all aspects of the property market but one area where the impact of uncertainty is particularly significant is within feasibility analyses. Any development is impacted by differences between market conditions at the conception of the project and the market realities at the time of completion. The feasibility study needs to address the possible outcomes based on an understanding of the current market. This requires the appraiser to forecast the most likely outcome relating to the sale price of the completed development, the construction costs and the timing of both. It also requires the appraiser to understand the impact of finance on the project. All these issues are time sensitive and analysis needs to be undertaken to show the impact of time to the viability of the project. The future is uncertain and a full feasibility analysis should be able to model the upside and downside risk pertaining to a range of possible outcomes. Feasibility studies are extensively used in Italy to determine land value but they tend to be single point analysis based upon a single set of “likely” inputs. In this paper we look at the practical impact of uncertainty in variables using a simulation model (Crystal Ball ©) with an actual case study of an urban redevelopment plan for an Italian Municipality. This allows the appraiser to address the issues of uncertainty involved and thus provide the decision maker with a better understanding of the risk of development. This technique is then refined using a “two-dimensional technique” to distinguish between “uncertainty” and “variability” and thus create a more robust model.

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Valuation is the process of estimating price. The methods used to determine value attempt to model the thought processes of the market and thus estimate price by reference to observed historic data. This can be done using either an explicit model, that models the worth calculation of the most likely bidder, or an implicit model, that that uses historic data suitably adjusted as a short cut to determine value by reference to previous similar sales. The former is generally referred to as the Discounted Cash Flow (DCF) model and the latter as the capitalisation (or All Risk Yield) model. However, regardless of the technique used, the valuation will be affected by uncertainties. Uncertainty in the comparable data available; uncertainty in the current and future market conditions and uncertainty in the specific inputs for the subject property. These input uncertainties will translate into an uncertainty with the output figure, the estimate of price. In a previous paper, we have considered the way in which uncertainty is allowed for in the capitalisation model in the UK. In this paper, we extend the analysis to look at the way in which uncertainty can be incorporated into the explicit DCF model. This is done by recognising that the input variables are uncertain and will have a probability distribution pertaining to each of them. Thus buy utilising a probability-based valuation model (using Crystal Ball) it is possible to incorporate uncertainty into the analysis and address the shortcomings of the current model. Although the capitalisation model is discussed, the paper concentrates upon the application of Crystal Ball to the Discounted Cash Flow approach.

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Following the attack on the World Trade Center on 9/11 volatility of daily returns of the US stock market rose sharply. This increase in volatility may reflect fundamental changes in the economic determinants of prices such as expected earnings, interest rates, real growth and inflation. Alternatively, the increase in volatility may simply reflect the effects of increased uncertainty in the financial markets. This study therefore sets out to determine if the effects of the attack on the World Trade Center on 9/11 had a fundamental or purely financial impact on US real estate returns. In order to do this we compare pre- and post-9/11 crisis returns for a number of US REIT indexes using an approach suggested by French and Roll (1986), as extended by Tuluca et al (2003). In general we find no evidence that the effects of 9/11 had a fundamental effect on REIT returns. In other words, we find that the effect of the attack on the World Trade Center on 9/11 had only a financial effect on REIT returns and therefore was transitory.

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Research on the topic of liquidity has greatly benefited from the improved availability of data. Researchers have addressed questions regarding the factors that influence bid-ask spreads and the relationship between spreads and risk, return and liquidity. Intra-day data have been used to measure the effective spread and researchers have been able to refine the concepts of liquidity to include the price impact of transactions on a trade-by-trade analysis. The growth in the creation of tax-transparent securities has greatly enhanced the visibility of securitized real estate, and has naturally led to the question of whether the increased visibility of real estate has caused market liquidity to change. Although the growth in the public market for securitized real estate has occurred in international markets, it has not been accompanied by universal publication of transaction data. Therefore this paper develops an aggregate daily data-based test for liquidity and applies the test to US data in order to check for consistency with the results of prior intra-day analysis. If the two approaches produce similar results, we can apply the same technique to markets in which less detailed data are available and offer conclusions on the liquidity of a wider set of markets.

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This paper uses data provided by three major real estate advisory firms to investigate the level and pattern of variation in the measurement of historic real estate rental values for the main European office centres. The paper assesses the extent to which the data providing organizations agree on historic market performance in terms of returns, risk and timing and examines the relationship between market maturity and agreement. The analysis suggests that at the aggregate level and for many markets, there is substantial agreement on direction, quantity and timing of market change. However, there is substantial variability in the level of agreement among cities. The paper also assesses whether the different data sets produce different explanatory models and market forecast. It is concluded that, although disagreement on the direction of market change is high for many market, the different data sets often produce similar explanatory models and predict similar relative performance.

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This paper explores in particular how Teikei groups, as forms of Community Supported Agriculture (CSA), operate in Japan, focussing on one particular group. The paper links the Teikei approach to debates around social capital and consumer-citizenship, arguing that pre-existing consumer/citizen institutions may usefully be engaged in developing food citizenship and CSA operations. The discussion is linked to CSA and various other alternative food networks (AFNs) that have grown up in various forms in Japan, the US, the UK and elsewhere in Europe over the past thirty years or so. CSA in similar fashion to Teikei involves bringing producers and consumers closer together in terms of reconnecting the agricultural producer and consumer to aid food traceability and quality (including organic). CSA also exhibits elements of new assemblies of agricultural governance based on enhanced consumer-citizenship where consumers, to varying degrees, have a say in what and how produce is grown and how the land is managed.

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This paper re-examines the relative importance of sector and regional effects in determining property returns. Using the largest property database currently available in the world, we decompose the returns on individual properties into a national effect, common to all properties, and a number of sector and regional factors. However, unlike previous studies, we categorise the individual property data into an ever-increasing number of property-types and regions, from a simple 3-by-3 classification, up to a 10 by 63 sector/region classification. In this way we can test the impact that a finer classification has on the sector and regional effects. We confirm the earlier findings of previous studies that sector-specific effects have a greater influence on property returns than regional effects. We also find that the impact of the sector effect is robust across different classifications of sectors and regions. Nonetheless, the more refined sector and regional partitions uncover some interesting sector and regional differences, which were obscured in previous studies. All of which has important implications for property portfolio construction and analysis.

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This paper sets out the findings of a group of research and development projects carried out at the Department of Real Estate & Planning at the University of Reading and at Oxford Property Systems over the period 1999 – 2003. The projects have several aims: these are to identify the fundamental drivers of the pricing of different lease terms in the UK property sector; to identify current and best market practice and uncover the main variations in lease terms; to identify key issues in pricing lease terms; and to develop a model for the pricing of rent under a variety of lease variations. From the landlord’s perspective, the main factors driving the required ‘compensation’ for a lease term amendment include expected rental volatility, expected probability of tenant vacation, and the expected costs of tenant vacation. These data are used in conjunction with simulation technology to reflect the options inherent in certain lease types to explore the required rent adjustment. The resulting cash flows have interesting qualities which illustrate the potential importance of option pricing in a non-complex and practical way.