891 resultados para No return


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The next generation consumer level interactive services require reliable and constant communication for both mobile and static users. The Digital Video Broadcasting ( DVB) group has exploited the rapidly increasing satellite technology for the provision of interactive services and launched a standard called Digital Video Broadcast through Return Channel Satellite (DYB-RCS). DVB-RCS relies on DVB-Satellite (DVB-S) for the provision of forward channel. The Digital Signal processing (DSP) implemented in the satellite channel adapter block of these standards use powerful channel coding and modulation techniques. The investigation is concentrated towards the Forward Error Correction (FEC) of the satellite channel adapter block, which will help in determining, how the technology copes with the varying channel conditions and user requirements(1).

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Efficient markets should guarantee the existence of zero spreads for total return swaps. However, real estate markets have recorded values that are significantly different from zero in both directions. Possible explanations might suggest non-rational behaviour by inexperienced market players or unusual features of the underlying asset market. We find that institutional characteristics in the underlying market lead to market inefficiencies and, hence, to the creation of a rational trading window with upper and lower bounds within which transactions do not offer arbitrage opportunities. Given the existence of this rational trading window, we also argue that the observed spreads can substantially be explained by trading imbalances due to the limited liquidity of a newly formed market and/or to the effect of market sentiment, complementing explanations based on the lag between underlying market returns and index returns.

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This article presents and contextualises a newly-discovered letter by Thomas Hardy, housed in the Chatto & Windus archive at the University of Reading. The letter sheds new light on the publishing history of Hardy's novel 'The return of the native'

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Global financial activity is heavily concentrated in a small number of world cities –international financial centers. The office markets in those cities receive significant flows of investment capital. The growing specialization of activity in IFCs and innovations in real estate investment vehicles lock developer, occupier, investment, and finance markets together, creating common patterns of movement and transmitting shocks from one office market throughout the system. International real estate investment strategies that fail to recognize this common source of volatility and risk may fail to deliver the diversification benefits sought.

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Depreciation is a key element of understanding the returns from and price of commercial real estate. Understanding its impact is important for asset allocation models and asset management decisions. It is a key input into well-constructed pricing models and its impact on indices of commercial real estate prices needs to be recognised. There have been a number of previous studies of the impact of depreciation on real estate, particularly in the UK. Law (2004) analysed all of these studies and found that the seemingly consistent results were an illusion as they all used a variety of measurement methods and data. In addition, none of these studies examined impact on total returns; they examined either rental value depreciation alone or rental and capital value depreciation. This study seeks to rectify this omission, adopting the best practice measurement framework set out by Law (2004). Using individual property data from the UK Investment Property Databank for the 10-year period between 1994 and 2003, rental and capital depreciation, capital expenditure rates, and total return series for the data sample and for a benchmark are calculated for 10 market segments. The results are complicated by the period of analysis which started in the aftermath of the major UK real estate recession of the early 1990s, but they give important insights into the impact of depreciation in different segments of the UK real estate investment market.

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Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.

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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 prior research on the structure and performance of UK real estate portfolios has relied on aggregated measures for sector and region. For these groupings to have validity, the performance of individual properties within each group should be similar. This paper analyses a sample of 1,200 properties using multiple discriminant analysis and cluster analysis techniques. It is shown that conventional property type and spatial classifications do not capture the variation in return behaviour at the individual building level. The major feature is heterogeneity - but there may be distinctions between growth and income properties and between single and multi-let properties that could help refine portfolio structures.

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It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models.

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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.