943 resultados para Repeated Averages of Real-Valued Functions
Resumo:
The recent poor performance of the equity market in the UK has meant that real estate is increasingly been seen as an attractive addition to the mixed-asset portfolio. However, determining whether the good return enjoyed by real estate is a temporary or long-term phenomenon is a question that remains largely unanswered. In other words, there is little or no evidence to indicate whether real estate should play a consistent role in the mixed-asset portfolio over short- and long-term investment horizons. Consistency in this context refers to the ability of an asset to maintain a positive allocation in an efficient portfolio over different holding periods. Such consistency is a desirable trait for any investment, but takes on particular significance when real estate is considered, as the asset class is generally perceived to be a long-term investment due to illiquidity. From an institutional investor’s perspective, it is therefore crucial to determine whether real estate can be reasonably expected to maintain a consistent allocation in the mixed-asset portfolio in both the short and long run and at what percentage. To address the question of consistency the allocation of real estate in the mixed-asset portfolio was calculated over different holding periods varying from 5- to 25-years.
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This paper contributes to a fast growing literature which introduces game theory in the analysis of real option investments in a competitive setting. Specifically, in this paper we focus on the issue of multiple equilibria and on the implications that different equilibrium selections may have for the pricing of real options and for subsequent strategic decisions. We present some theoretical results of the necessary conditions to have multiple equilibria and we show under which conditions different tie-breaking rules result in different economic decisions. We then present a numerical exercise using the in formation set obtained on a real estate development in South London. We find that risk aversion reduces option value and this reduction decreases marginally as negative externalities decrease.
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Modern Portfolio Theory (MPT) has been advocated as a more rational approach to the construction of real estate portfolios. The application of MPT can now be achieved with relative ease using the powerful facilities of modern spreadsheet, and does not necessarily need specialist software. This capability is to be found in the use of an add-in Tool now found in several spreadsheets, called an Optimiser or Solver. The value in using this kind of more sophisticated analysis feature of spreadsheets is increasingly difficult to ignore. This paper examines the use of the spreadsheet Optimiser in handling asset allocation problems. Using the Markowitz Mean-Variance approach, the paper introduces the necessary calculations, and shows, by means of an elementary example implemented in Microsoft's Excel, how the Optimiser may be used. Emphasis is placed on understanding the inputs and outputs from the portfolio optimisation process, and the danger of treating the Optimiser as a Black Box is discussed.
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The IPD Annual Index is the largest and most comprehensive Real Estate market index available in the UK Such coverage however inevitably leads to delays in publication. In contrast there are a number of quarterly and monthly indices which are published within days of the year end but which lack the coverage in terms of size and numbers of properties. This paper analyses these smaller but more timely indices to see whether such indices can be used to predict the performance of the IPD Annual Index. Using a number of measures of forecasting accuracy it is shown that the smaller indices provide unbiased and efficient predictions of the IPD Annual Index. Such indices also significantly outperform a naive no-change model. Although no one index performs significantly better than the others. The more timely indices however do not perfectly track the IPD Annual Index. As a result any short run predictions of performance will be subject to a degree of error. Nevertheless the more timely indices, although lacking authoritative coverage, provide a valuable service to investors giving good estimates of Real Estates performance well before the publication of the IPD Annual Index.
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In this paper, we extend to the time-harmonic Maxwell equations the p-version analysis technique developed in [R. Hiptmair, A. Moiola and I. Perugia, Plane wave discontinuous Galerkin methods for the 2D Helmholtz equation: analysis of the p-version, SIAM J. Numer. Anal., 49 (2011), 264-284] for Trefftz-discontinuous Galerkin approximations of the Helmholtz problem. While error estimates in a mesh-skeleton norm are derived parallel to the Helmholtz case, the derivation of estimates in a mesh-independent norm requires new twists in the duality argument. The particular case where the local Trefftz approximation spaces are built of vector-valued plane wave functions is considered, and convergence rates are derived.
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Scale functions play a central role in the fluctuation theory of spectrally negative Lévy processes and often appear in the context of martingale relations. These relations are often require excursion theory rather than Itô calculus. The reason for the latter is that standard Itô calculus is only applicable to functions with a sufficient degree of smoothness and knowledge of the precise degree of smoothness of scale functions is seemingly incomplete. The aim of this article is to offer new results concerning properties of scale functions in relation to the smoothness of the underlying Lévy measure. We place particular emphasis on spectrally negative Lévy processes with a Gaussian component and processes of bounded variation. An additional motivation is the very intimate relation of scale functions to renewal functions of subordinators. The results obtained for scale functions have direct implications offering new results concerning the smoothness of such renewal functions for which there seems to be very little existing literature on this topic.
The impact of information and communications technology on commercial real estate in the new economy
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Purpose – This paper seeks to critically review the conceptual frameworks that have been developed for assessing the impact of information and communications technology (ICT) on real estate. Design/methodology/approach – The research is based on a critical review of existing literature and draws from examples of previous empirical research in the field. Findings – The paper suggests that a “socio-technical framework” is more appropriate to examine ICT impact in real estate than other “deterministic” frameworks. Therefore, ICT is an important part of the new economy, but must be seen in the context of a number of other social and economic factors. Research limitations/implications – The research is based on a qualitative assessment of existing frameworks, and by using examples from commercial real estate, assesses the extent to which a “socio-technical” framework can aid understanding of ICT impact. Practical implications – The paper is important in highlighting a number of the main issues in conceptualising ICT impact in real estate and also critically examines the emergence of a new economy in the information society within the general context of real estate. The paper also highlights research gaps in the field. Originality/value – The paper deconstructs the myths of the “death of real estate” and “productivity increase means jobs loss”, in relation to office real estate. Finally, it examines some of the ways in which ICT is impacting on real estate and suggests the most important components for a future research agenda in the field of ICT and real estate impact, and will be of value to property investors, facilities managers, developers, financiers, and others.
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This article summarizes the main research findings from the first of a series of annual surveys conducted for the British Council of Shopping Centres. The study examines the changing pattern of retailing in the United Kingdom and provides an overview of key research from previous studies in both the U.K. and the United States. The main findings are then presented, including an examination of the impact of e-commerce on sales and rental values and on the future space and ownership / leasing requirements of U.K. retailers for 2000-2005. The impact on a shopping center in a case study town in the U.K. is also considered. The difficulties of isolating the impact of e-commerce from other forces for change in retailing are highlighted. In contrast to other viewpoints, the results show that e-commerce will not mean the death of conventional store-based U.K. retailing, although further benchmark research is needed.
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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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We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.
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There are no direct observational methods for determining the total rate at which energy is extracted from the solar wind by the magnetosphere. In the absence of such a direct measurement, alternative means of estimating the energy available to drive the magnetospheric system have been developed using different ionospheric and magnetospheric indices as proxies for energy consumption and dissipation and thus the input. The so-called coupling functions are constructed from the parameters of the interplanetary medium, as either theoretical or empirical estimates of energy transfer, and the effectiveness of these coupling functions has been evaluated in terms of their correlation with the chosen index. A number of coupling functions have been studied in the past with various criteria governing event selection and timescale. The present paper contains an exhaustive survey of the correlation between geomagnetic activity and the near-Earth solar wind and two of the planetary indices at a wide variety of timescales. Various combinations of interplanetary parameters are evaluated with careful allowance for the effects of data gaps in the interplanetary data. We show that the theoretical coupling, P�, function first proposed by Vasyliunas et al. is superior at all timescales from 1-day to 1-year.
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This paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.
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We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.
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Using a variation of the Nelson-Siegel term structure model we examine the sensitivity of real estate securities in six key global markets to unexpected changes in the level, slop and curvature of the yield curve. Our results confirm the time-sensitive nature of the exposure and sensitivity to interest rates and highlight the importance of considering the entire term structure of interest rates. One issue that is of particular of interest is that despite the 2007-9 financial crisis the importance of unanticipated interest rate risk weakens post 2003. Although the analysis does examine a range of markets the empirical analysis is unable to provide definitive evidence as to whether REIT and property-company markets display heightened or reduced exposure.