Measuring the impact of short and lending practices using the DGTW benchmarks

Mutual fund managers increasingly lend their holdings and/or use short sales to generate higher returns for their funds. This project presents a first look into the impact these practices on performance using the performance measures: i) Characteristic Selectivity (CS), the ability of the fund's managers to choose stocks that outperform their benchmarks; ii) Characteristic Timing (CT), the ability of the manager to time the market; iii) and Average Style (AS), the returns from funds systematically holding stocks with certain characteristics. These returns are computed through the DGTW benchmarks. The effect of other variables that have also been shown to impact fund’s returns – total net assets under management, investment styles, turnover and expense ratios – will also be analyzed. I find that managers who use short-sales do not exhibit better stock picking abilities than those who do not, while mutual funds that lend do present higher CS returns. In addition, while lending is not significant for the total performance of a fund, the employment of short-sales and of both short-sales and lending has a negative impact on the fund’s performance.

Development of benchmarks for operating costs and resources consumption to be used in healthcare building sustainability assessment methods

Since the last decade of the twentieth century, the healthcare industry is paying attention to the environmental impact of their buildings and therefore new regulations, policy goals and Buildings Sustainability Assessment (HBSA) methods are being developed and implemented. At the present, healthcare is one of the most regulated industries and it is also one of the largest consumers of energy per net floor area. To assess the sustainability of healthcare buildings it is necessary to establish a set of benchmarks related with their life-cycle performance. They are both essential to rate the sustainability of a project and to support designers and other stakeholders in the process of designing and operating a sustainable building, by allowing the comparison to be made between a project and the conventional and best market practices. This research is focused on the methodology to set the benchmarks for resources consumption, waste production, operation costs and potential environmental impacts related to the operational phase of healthcare buildings. It aims at contributing to the reduction of the subjectivity found in the definition of the benchmarks used in Building Sustainability Assessment (BSA) methods, and it is applied in the Portuguese context. These benchmarks will be used in the development of a Portuguese HBSA method.

Benchmarks i mètriques d'avaluació de plataformes encastades multimèdia

Aquest projecte compara les possibilitats per a aplicacions multimèdia d'algunes de les arquitectures de processador que podem trobar en sistemes encastats. Per fer-ho s'ha seleccionat una sèrie de benchmarks que inclouen una mostra d'aplicacions multimèdia, així com un conjunt de benchmarks que ens permet mesurar aspectes d'un sistema operatiu GNU/Linux. També s'ha determinat quines haurien de ser les principals mètriques a considerar en el context dels sistemes encastats.

Access to a simulator is not enough: the benefits of virtual reality training based on peer-group-derived benchmarks--a randomized controlled trial.

BACKGROUND: Virtual reality (VR) simulators are widely used to familiarize surgical novices with laparoscopy, but VR training methods differ in efficacy. In the present trial, self-controlled basic VR training (SC-training) was tested against training based on peer-group-derived benchmarks (PGD-training). METHODS: First, novice laparoscopic residents were randomized into a SC group (n = 34), and a group using PGD-benchmarks (n = 34) for basic laparoscopic training. After completing basic training, both groups performed 60 VR laparoscopic cholecystectomies for performance analysis. Primary endpoints were simulator metrics; secondary endpoints were program adherence, trainee motivation, and training efficacy. RESULTS: Altogether, 66 residents completed basic training, and 3,837 of 3,960 (96.8 %) cholecystectomies were available for analysis. Course adherence was good, with only two dropouts, both in the SC-group. The PGD-group spent more time and repetitions in basic training until the benchmarks were reached and subsequently showed better performance in the readout cholecystectomies: Median time (gallbladder extraction) showed significant differences of 520 s (IQR 354-738 s) in SC-training versus 390 s (IQR 278-536 s) in the PGD-group (p < 0.001) and 215 s (IQR 175-276 s) in experts, respectively. Path length of the right instrument also showed significant differences, again with the PGD-training group being more efficient. CONCLUSIONS: Basic VR laparoscopic training based on PGD benchmarks with external assessment is superior to SC training, resulting in higher trainee motivation and better performance in simulated laparoscopic cholecystectomies. We recommend such a basic course based on PGD benchmarks before advancing to more elaborate VR training.

Edge matching puzzles as hard SAT/CSP benchmarks

Recently, edge matching puzzles, an NP-complete problem, have rececived, thanks to money-prized contests, considerable attention from wide audiences. We consider these competitions not only a challenge for SAT/CSP solving techniques but also as an opportunity to showcase the advances in the SAT/CSP community to a general audience. This paper studies the NP-complete problem of edge matching puzzles focusing on providing generation models of problem instances of variable hardness and on its resolution through the application of SAT and CSP techniques. From the generation side, we also identify the phase transition phenomena for each model. As solving methods, we employ both; SAT solvers through the translation to a SAT formula, and two ad-hoc CSP solvers we have developed, with different levels of consistency, employing several generic and specialized heuristics. Finally, we conducted an extensive experimental investigation to identify the hardest generation models and the best performing solving techniques.

Benchmarks en cámaras de comercio del mundo

Banco del conocimiento

Estudio: Benchmarks en cámaras de comercio del mundo para cada UEN: entendimiento del cliente

Banco del conocimiento

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.

The assessment of benchmarks executed on bare-metal and using para-virtualization

A full assessment of para-­virtualization is important, because without knowledge about the various overheads, users can not understand whether using virtualization is a good idea or not. In this paper we are very interested in assessing the overheads of running various benchmarks on bare-­‐metal, as well as on para-­‐virtualization. The idea is to see what the overheads of para-­‐ virtualization are, as well as looking at the overheads of turning on monitoring and logging. The knowledge from assessing various benchmarks on these different systems will help a range of users understand the use of virtualization systems. In this paper we assess the overheads of using Xen, VMware, KVM and Citrix, see Table 1. These different virtualization systems are used extensively by cloud-­‐users. We are using various Netlib1 benchmarks, which have been developed by the University of Tennessee at Knoxville (UTK), and Oak Ridge National Laboratory (ORNL). In order to assess these virtualization systems, we run the benchmarks on bare-­‐metal, then on the para-­‐virtualization, and finally we turn on monitoring and logging. The later is important as users are interested in Service Level Agreements (SLAs) used by the Cloud providers, and the use of logging is a means of assessing the services bought and used from commercial providers. In this paper we assess the virtualization systems on three different systems. We use the Thamesblue supercomputer, the Hactar cluster and IBM JS20 blade server (see Table 2), which are all servers available at the University of Reading. A functional virtualization system is multi-­‐layered and is driven by the privileged components. Virtualization systems can host multiple guest operating systems, which run on its own domain, and the system schedules virtual CPUs and memory within each Virtual Machines (VM) to make the best use of the available resources. The guest-­‐operating system schedules each application accordingly. You can deploy virtualization as full virtualization or para-­‐virtualization. Full virtualization provides a total abstraction of the underlying physical system and creates a new virtual system, where the guest operating systems can run. No modifications are needed in the guest OS or application, e.g. the guest OS or application is not aware of the virtualized environment and runs normally. Para-­‐virualization requires user modification of the guest operating systems, which runs on the virtual machines, e.g. these guest operating systems are aware that they are running on a virtual machine, and provide near-­‐native performance. You can deploy both para-­‐virtualization and full virtualization across various virtualized systems. Para-­‐virtualization is an OS-­‐assisted virtualization; where some modifications are made in the guest operating system to enable better performance. In this kind of virtualization, the guest operating system is aware of the fact that it is running on the virtualized hardware and not on the bare hardware. In para-­‐virtualization, the device drivers in the guest operating system coordinate the device drivers of host operating system and reduce the performance overheads. The use of para-­‐virtualization [0] is intended to avoid the bottleneck associated with slow hardware interrupts that exist when full virtualization is employed. It has revealed [0] that para-­‐ virtualization does not impose significant performance overhead in high performance computing, and this in turn this has implications for the use of cloud computing for hosting HPC applications. The “apparent” improvement in virtualization has led us to formulate the hypothesis that certain classes of HPC applications should be able to execute in a cloud environment, with minimal performance degradation. In order to support this hypothesis, first it is necessary to define exactly what is meant by a “class” of application, and secondly it will be necessary to observe application performance, both within a virtual machine and when executing on bare hardware. A further potential complication is associated with the need for Cloud service providers to support Service Level Agreements (SLA), so that system utilisation can be audited.

Benchmarks and the accuracy of GARCH model estimation

This paper reviews nine software packages with particular reference to their GARCH model estimation accuracy when judged against a respected benchmark. We consider the numerical consistency of GARCH and EGARCH estimation and forecasting. Our results have a number of implications for published research and future software development. Finally, we argue that the establishment of benchmarks for other standard non-linear models is long overdue.

A review of existing building benchmarks and the development of a set of reference office buildings for England and Wales

The modern built environment has become more complex in terms of building types, environmental systems and use profiles. This complexity causes difficulties in terms of optimising buildings energy design. In this circumstance, introducing a set of prototype reference buildings, or so called benchmark buildings, that are able to represent all or majority parts of the UK building stock may be useful for the examination of the impact of national energy policies on building energy consumption. This study proposes a set of reference office buildings for England and Wales based on the information collected from the Non-Domestic Building Stock (NDBS) project and an intensive review of the existing building benchmarks. The proposed building benchmark comprises 10 prototypical reference buildings, which in relation to built form and size, represent 95% of office buildings in England and Wales. This building benchmark provides a platform for those involved in building energy simulations to evaluate energy-efficiency measures and for policy-makers to assess the influence of different building energy policies.

How do I know if my forecasts are better? Using benchmarks in Hydrological ensemble prediction

The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are ‘toughest to beat’ and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all catchment sizes. Simpler meteorological benchmarks are particularly useful for high flows. Recommendations for EFAS are to move to routine use of meteorological persistency, an advanced meteorological benchmark and a simple meteorological benchmark in order to provide a robust evaluation of forecast skill. This work provides the first comprehensive evidence on how benchmarks can be used in evaluation of skill in probabilistic hydrological forecasts and which benchmarks are most useful for skill discrimination and avoidance of naïve skill in a large scale HEPS. It is recommended that all HEPS use the evidence and methodology provided here to evaluate which benchmarks to employ; so forecasters can have trust in their skill evaluation and will have confidence that their forecasts are indeed better.