998 resultados para Property Diversification


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Timberland is seen as a long-term investment which has recently received increased institutional investor attention in many countries and potentially provides added value in a mixed-asset portfolio. Using the National Council of Real Estate Investment Fiduciaries (NCREIF) timberland series, this paper analyses the risk-adjusted performance and portfolio diversification benefits of timberland in the United States over the period of 1987-2007. U.S. timberland is seen to have been a strongly performed asset class with significant portfolio diversification benefits over this period; with a significant portfolio role separate to that of real estate. However, recent years have seen reduced risk-adjusted returns, with some loss of portfolio diversification benefits of timberland with stocks and real estate. Global drivers are likely to see increased future demand for timberland investment.

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This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

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t is well known that when assets are randomly-selected and combined in equal proportions in a portfolio, the risk of the portfolio declines as the number of different assets increases without affecting returns. In other words, increasing portfolio size should improve the risk/return trade-off compared with a portfolio of asset size one. Therefore, diversifying among several property funds may be a better alternative for investors compared to holding only one property fund. Nonetheless, it also well known that with naïve diversification although risk always decreases with portfolio size, it does so at a decreasing rate so that at some point the reduction in portfolio risk, from adding another fund, becomes negligible. Based on this fact, a reasonable question to ask is how much diversification is enough, or in other words, how many property funds should be included in a portfolio to minimise return volatility.

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The issue of diversification in direct real estate investment portfolios has been widely studied in academic and practitioner literature. Most work, however, has been done using either partially aggregated data or data for small samples of individual properties. This paper reports results from tests of both risk reduction and diversification that use the records of 10,000+ UK properties tracked by Investment Property Databank. It provides, for the first time, robust estimates of the diversification gains attainable given the returns, risks and cross‐correlations across the individual properties available to fund managers. The results quantify the number of assets and amount of money needed to construct both ‘balanced’ and ‘specialist’ property portfolios by direct investment. Target numbers will vary according to the objectives of investors and the degree to which tracking error is tolerated. The top‐level results are consistent with previous work, showing that a large measure of risk reduction can be achieved with portfolios of 30–50 properties, but full diversification of specific risk can only be achieved in very large portfolios. However, the paper extends previous work by demonstrating on a single, large dataset the implications of different methods of calculating risk reduction, and also by showing more disaggregated results relevant to the construction of specialist, sector‐focussed funds.

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Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD UK database over the period 1981 to 2003 than normally distributed risk models. This finding mirrors results in the US and Australia using identical methodology. Real estate investment risk is heteroskedastic, but the characteristic exponent of the investment risk function is constant across time – yet it 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. The results, therefore, indicate that multi‐risk factor portfolio allocation models based on measures of investment codependence from finite‐variance statistics are ineffective in the real estate context

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Much of the literature on the construction of mixed asset portfolios and the case for property as a risk diversifier rests on correlations measured over the whole of a given time series. Recent developments in finance, however, focuses on dependence in the tails of the distribution. Does property offer diversification from equity markets when it is most needed - when equity returns are poor. The paper uses an empirical copula approach to test tail dependence between property and equity for the UK and for a global portfolio. Results show strong tail dependence: in the UK, the dependence in the lower tail is stronger than in the upper tail, casting doubt on the defensive properties of real estate stocks.

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The number of properties to hold to achieve a well-diversified real estate property portfolio presents a puzzle, as the estimated number is considerably higher than that seen in actual portfolios. However, Statman (1987) argues that investors should only increase the number of holdings as long as the marginal benefits of diversification exceed their costs. Using this idea we find that the marginal benefits of diversification in real estate portfolios are so small that investors are probably rational in holding small portfolios, at least as far as the reduction in standard deviation is concerned.

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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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Property portfolio diversification takes many forms, most of which can be associated with asset size. In other words larger property portfolios are assumed to have greater diversification potential than small portfolios. In addition, since greater diversification is generally associated with lower risk it is assumed that larger property portfolios will also have reduced return variability compared with smaller portfolios. If large property portfolios can simply be regarded as scaled-up, better-diversified versions of small property portfolios, then the greater a portfolio’s asset size, the lower its risk. This suggests a negative relationship between asset size and risk. However, if large property portfolios are not simply scaled-up versions of small portfolios, the relationship between asset size and risk may be unclear. For instance, if large portfolios hold riskier assets or pursue more volatile investment strategies, it may be that a positive relationship between asset size and risk would be observed, even if large property portfolios are more diversified. This paper tests the empirical relationship between property portfolio size, diversification and risk, in Institutional portfolios in the UK, during the period from 1989 to 1999 to determine which of these two characterisations is more appropriate.