Domestic and foreign bias in global real estate mutual fund investment allocations

The purpose of the study is to seek a better understanding of the investment allocation behaviour of the real estate mutual funds by focusing on asset allocation at the country level. Analysing the country allocation of 553 real estate mutual funds domiciled in 20 countries, we attempt to trace how investment bias exists across countries and affects their country allocations. Our results evidence the existence of disproportionate country allocation to their domestic markets (domestic bias) and to each foreign market (foreign bias). We also find each bias is influenced by different sets of variables: real estate market influences for domestic bias and familiarity influences for foreign bias. This difference in factors influential for each bias in part explains the conflated relationship between the two biases.

Real estate mutual funds: herding, momentum-trading and performance

This study jointly examines herding, momentum trading and performance in real estate mutual funds (REMFs). We do this using trading and performance data for 159 REMFs across the period 1998–2008. In support of the view that Real Estate Investment Trust (REIT) stocks are relatively more transparent, we find that stock herding by REMFs is lower in REIT stocks than other stock. Herding behavior in our data reveals a tendency for managers to sell winners, reflective of the “disposition effect.” We find low overall levels of REMF momentum trading, but further evidence of the disposition effect when momentum trading is segregated into buy–sell dimensions. We test the robustness of our analysis using style analysis, and by reference to the level of fund dividend distribution. Our results for this are consistent with our conjecture about the role of transparency in herding, but they provide no new insights in relation to the momentum-trading dimensions of our analysis. Summarizing what are complex interrelationships, we find that neither herding nor momentum trading are demonstrably superior investment strategies for REMFs.

Toward a new generation of world climate research and computing facilities

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather–climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology.

Discerning policy and drivers for sustainable facilities management practice

Due to the changing nature of the facilities management (FM) profession, facilities managers are increasingly engaged with the evolving sustainability agenda in the UK and the development or uptake of sustainability policies within their organisations. This study investigates how facilities managers are engaging with the sustainability agenda and the drivers, policy issues and information they use to improve their sustainability performance management. A web based self-administered questionnaire survey of facilities managers in the UK was conducted to identify drivers and issues that influence and support good sustainable practices. A total of 268 facilities managers responded. The results indicate that legislation is the most important driver for the implementation of sustainable practices. Corporate image and Organisational ethos are also recognised. However demand for efficient monitoring, management and reporting on environmental impact is not highly rated even though the top three issues of sustainability managed by facilities managers are energy management, waste and recycling management and carbon footprint. In addition, facilities managers are expected to take ownership of activities assigned to the reduction of carbon emission. Government industries and organisation with high turnover are more likely to have a sustainability policy. Financial constraints are the main barriers while legislations are the main driver for implementing sustainability. For non-profit organisations and the charitable sector, financial constraints are no hindrance to implementing a sustainability policy. The conclusion drawn is that sustainability agendas continue to be influenced by regulated environmental issues rather than a balanced approach which takes into consideration the wider social and economic aspects of sustainability. While this scenario is far from ideal, the expectation is that the organisation will trust FM to take a vital role in delivering a comprehensive sustainability policy due to the rising tide of legislation, public scrutiny, as well as the needed business case for genuinely embracing sustainability. However, as the integration of sustainability with core business strategies is continuously evolving the emphasis on different drivers will vary from organisation to organisation as well as the responsibilities of facilities managers.

Mutual binding of polymer end-groups by complementary π–π-stacking: a molecular “Roman Handshake”

Self-complementary tweezer-molecules based on a naphthalenediimide core self-assemble into supramolecular dimers through mutual π–π-stacking and hydrogen bonding. The resulting motif is extremely stable in solution (Ka = 105 M−1), and its attachment to one terminal position of a poly(ethylene glycol) chain leads to a doubling of the polymer's apparent molecular weight.

Facilities management carbon footprints: an audit of critical elements of management and reporting

Concern for the environmental impact of organizations’ activities has led to the recognition and demand for organizations to manage and report on their carbon footprint. However, there is no limit as to the areas of carbon footprints required in such annual environmental reports. To deliver improvements in the quality of carbon footprint management and reporting, there is a need to identify the main elements of carbon footprint strategy that can be endorsed, supported and encouraged by facility managers. The study investigates carbon footprint elements managed and reported upon by facility manager in the UK. Drawing on a questionnaire survey of 256 facility managers in the UK, the key elements of carbon footprints identified in carbon footprint reports are examined. The findings indicate that the main elements are building energy consumption, waste disposal and water consumption. Business travel in terms of using public transport, air travel and company cars are also recognized as important targets and objectives for the carbon footprint strategy of several FM (facilities management) organizations.

Transition from an anti-phase error-correction-mode to a synchronization mode in the mutual hand tracking

Proactive motion in hand tracking and in finger bending, in which the body motion occurs prior to the reference signal, was reported by the preceding researchers when the target signals were shown to the subjects at relatively high speed or high frequencies. These phenomena indicate that the human sensory-motor system tends to choose an anticipatory mode rather than a reactive mode, when the target motion is relatively fast. The present research was undertaken to study what kind of mode appears in the sensory-motor system when two persons were asked to track the hand position of the partner with each other at various mean tracking frequency. The experimental results showed a transition from a mutual error-correction mode to a synchronization mode occurred in the same region of the tracking frequency with that of the transition from a reactive error-correction mode to a proactive anticipatory mode in the mechanical target tracking experiments. Present research indicated that synchronization of body motion occurred only when both of the pair subjects operated in a proactive anticipatory mode. We also presented mathematical models to explain the behavior of the error-correction mode and the synchronization mode.

Mutual dependency grid for stakeholder mapping: a component-based approach to supply chain participant analysis

Stakeholder analysis plays a critical role in business analysis. However, the majority of the stakeholder identification and analysis methods focus on the activities and processes and ignore the artefacts being processed by human beings. By focusing on the outputs of the organisation, an artefact-centric view helps create a network of artefacts, and a component-based structure of the organisation and its supply chain participants. Since the relationship is based on the components, i.e. after the stakeholders are identified, the interdependency between stakeholders and the focal organisation can be measured. Each stakeholder is associated with two types of dependency, namely the stakeholder’s dependency on the focal organisation and the focal organisation’s dependency on the stakeholder. We identify three factors for each type of dependency and propose the equations that calculate the dependency indexes. Once both types of the dependency indexes are calculated, each stakeholder can be placed and categorised into one of the four groups, namely critical stakeholder, mutual benefits stakeholder, replaceable stakeholder, and easy care stakeholder. The mutual dependency grid and the dependency gap analysis, which further investigates the priority of each stakeholder by calculating the weighted dependency gap between the focal organisation and the stakeholder, subsequently help the focal organisation to better understand its stakeholders and manage its stakeholder relationships.

Mechanism for synchronized motion between two humans in mutual tapping experiments: Transition from alternative mode to synchronization mode

We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.

Islamic mutual funds' financial performance and international investment style: evidence from 20 countries

We pursue the first large-scale investigation of a strongly growing mutual fund type: Islamic funds. Based on an unexplored, survivorship bias-adjusted data set, we analyse the financial performance and investment style of 265 Islamic equity funds from 20 countries. As Islamic funds often have diverse investment regions, we develop a (conditional) three-level Carhart model to simultaneously control for exposure to different national, regional and global equity markets and investment styles. Consistent with recent evidence for conventional funds, we find Islamic funds to display superior learning in more developed Islamic financial markets. While Islamic funds from these markets are competitive to international equity benchmarks, funds from especially Western nations with less Islamic assets tend to significantly underperform. Islamic funds’ investment style is somewhat tilted towards growth stocks. Funds from predominantly Muslim economies also show a clear small cap preference. These results are consistent over time and robust to time varying market exposures and capital market restrictions.

Biologically-inspired robust motion segmentation using mutual information

This paper presents a neuroscience inspired information theoretic approach to motion segmentation. Robust motion segmentation represents a fundamental first stage in many surveillance tasks. As an alternative to widely adopted individual segmentation approaches, which are challenged in different ways by imagery exhibiting a wide range of environmental variation and irrelevant motion, this paper presents a new biologically-inspired approach which computes the multivariate mutual information between multiple complementary motion segmentation outputs. Performance evaluation across a range of datasets and against competing segmentation methods demonstrates robust performance.

A radial basis function network classifier to maximise leave-one-out mutual information

tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.