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This paper focuses on execution costs as liquidity measure. Execution costs are related to volatility and are an important component of a firm’s cost of capital. The purpose of this paper is to examine whether emerging market firms have lower execution costs when they face less restrictions on foreign investment and when they have more foreign shareholders.

The authors begin by documenting the cross-sectional behavior of execution costs. The authors then obtain preliminary evidence on the interaction between execution costs, the investability index and actual foreign investment. These results foreshadow those the authors obtain with the regression analysis. The ordinary least square results show that more investable firms have lower execution costs after the authors control for firm size, stock price, return volatility, industry effects and country effects. This evidence is very robust and highly significant. Direct foreign ownership (FO) in emerging market firms also appear to be associated with lower execution costs. The economic benefit from lowering the investability index on trade execution costs is highly significant.

Using a large cross-sectional sample from 23 emerging markets, the authors show that firms with more ex ante restrictions on FO, measured by the investability index, have lower execution costs, such as quoted spreads (QS) and effective spreads (ES), after the authors control for firm size, stock price, return volatility, industry factors and country effects. In addition, direct FO in emerging market firms appears to be associated with lower execution costs. However, ex ante restrictions on FO dominate the influence of direct FO. For a 0.5 increase in the investability index in the range of 0–1, the QS will be reduced by 17 percent of the mean QS, and the ES will be reduced by 12 percent of the mean ES from the sample stocks.

There are important differences between the approach and most of the financial liberalization studies. First, whereas most of the earlier studies are conducted at the level of country or market analysis, the investigation is at the level of individual stocks. Second, the authors focus on a cross-sectional association that avoids a criticism leveled at time series analyses. Over-time studies often use specific time points to represent financial liberalization watersheds. This approach can be misleading when financial liberalizations are viewed as processes that unfold over time. Third, the proxies for financial openness are available not only for individual firms across markets, but the authors also make a distinction between potential and actual foreign investment. The authors further categorize actual foreign investment into direct and indirect FO.

The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs.

This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models.

The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment.

An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.

The purpose of this paper is to evaluate project activities' efficiency in different execution modes for the optimization of time–cost-quality and environmental impacts trade-off problem.

This paper presents a parallel Data Envelopment Analysis (DEA) method for evaluation of project activities with different execution modes to select the best execution mode and find a trade-off between objectives. Also, according to the nature of the project activities, outputs are categorized into desirable (quality) and undesirable (time, cost and environmental impacts) and analyzed based on the DEA model. In order to rank efficient execution modes, the ideal and anti-ideal virtual units method is used. The proposed model is implemented on a real case of a rural water supply construction project to demonstrate its validity.

The findings show that the use of the efficient execution mode in each activity leads to an optimal trade-off between the four project objectives (time, cost, quality and environmental impacts).

This study help project managers and practitioners with choosing the most efficient execution modes of project activities taking time–cost-quality-environmental impacts into account.

In this paper, in addition to time and cost optimization of construction projects, quality factors and environmental impacts are considered. Further to the authors' knowledge, there is no method for evaluating project activities' efficiency. The efficiency of different activity modes is also evaluated for the first time to select the most efficient modes. This research can assist project managers with choosing the most appropriate execution modes for the activities to ultimately accomplish the project with the lowest time, cost and environmental impacts along with the highest quality.

The purpose of this paper is to propose Extensible Markup Language (XML) data partitioning schemes that can cope with static and dynamic allocation for parallel holistic twig joins: grid metadata model for XML (GMX) and streams‐based partitioning method for XML (SPX).

GMX exploits the relationships between XML documents and query patterns to perform workload‐aware partitioning of XML data. Specifically, the paper constructs a two‐dimensional model with a document dimension and a query dimension in which each object in a dimension is composed from XML metadata related to the dimension. GMX provides a set of XML data partitioning methods that include document clustering, query clustering, document‐based refinement, query‐based refinement, and query‐path refinement, thereby enabling XML data partitioning based on the static information of XML metadata. In contrast, SPX explores the structural relationships of query elements and a range‐containment property of XML streams to generate partitions and allocate them to cluster nodes on‐the‐fly.

GMX provides several salient features: a set of partition granularities that balance workloads of query processing costs among cluster nodes statically; inter‐query parallelism as well as intra‐query parallelism at multiple extents; and better parallel query performance when all estimated queries are executed simultaneously to meet their probability of query occurrences in the system. SPX also offers the following features: minimal computation time to generate partitions; balancing skewed workloads dynamically on the system; producing higher intra‐query parallelism; and gaining better parallel query performance.

The current status of the proposed XML data partitioning schemes does not take into account XML data updates, e.g. new XML documents and query pattern changes submitted by users on the system.

Note that effectiveness of the XML data partitioning schemes mainly relies on the accuracy of the cost model to estimate query processing costs. The cost model must be adjusted to reflect characteristics of a system platform used in the implementation.

This paper proposes novel schemes of conducting XML data partitioning to achieve both static and dynamic workload balance.

The purpose of this paper is to propose a systematic study to formulate the cost of prototypes manufactured through rapid prototyping (RP) an fused deposition modeling (FDM) 3D printer in a university lab.

The paper has a theoretical‐conceptual approach. This approach is carried out by studying and proposing a methodology for calculating the cost of pieces prototyped an FDM 3D printer.

This work originated from a gap in literature to establish a way to calculate the price of RP pieces from FDM 3D printers in universities' labs, since no similar work has dealt with this RP technology and has not taken into account the costs of post‐processing step. The results suggest that the formulation may be used to calculate price of prototyped pieces through FDM 3D printer.

The systematic approach proposed by this research to formulate cost for the RP pieces is initially oriented only to modelling technique by FDM 3D printer. Considerations on operator's and designer's hourly rates are those practiced in Brazil, which may differ from other countries.

The paper's scientific contribution is a specific formulation to calculate price of prototyped pieces through FDM considering the post‐processing way, which differs from previous published works. The formulation implies that the execution times and the amount of material used were obtained by internal calculation of the tested machine. This is different from what has been already studied by previous literature which considers an index that encompasses the machine operation cost in function of time. It is aimed that the results obtained here are accurate, since error margins of the process variables are reduced.

The purpose of this paper is to investigate how insiders’ trades are executed and whether and how outside investors can mimic outperforming insiders and reap substantial portfolio returns that withstand the erosion from adjustments for both the standard factors and stock characteristics in the asset pricing literature.

The authors design a metric for measuring insiders’ trade execution quality: the trading alpha. The authors run regression analysis to control for trade difficulty, insider reputations and the corporate role ranks of insiders and document the existence of the abnormal trading alpha. The authors further form portfolios based on the abnormal trading alpha and document a significant abnormal return that is robust to both standard asset pricing factors model and the stock characteristics adjustments.

Outperforming insiders at the aggregate level resemble value investors who trade on long-term fundamental information, trade patiently and earn rents from providing liquidity. Outside investors can mimic the outperforming insiders and reap significant abnormal portfolio returns.

Data limitations on insider trades and their association/interaction with their brokers prevent us from having a conclusive investigation of the trading skill hypothesis. The authors hope to further research along the lines of the trading skill hypothesis as compared to investment style hypothesis with more detailed data about the brokers used by insiders.

The findings can be applied for money management profession in that outsider investors can monitor the trading execution and construct portfolios based on the adjusted abnormal trading alpha. The resulting portfolio has been documented to be highly profitable after risk adjustments using standard asset pricing factors as well as stock characteristics.

Professional money managers and outsider investors should be able to benefit from the findings in this paper and use the proposed trading alpha metric to construct and rebalance real-time investment portfolios.

Outperforming insiders at the aggregate level resemble value investors who act on long-term fundamental information, trade patiently and earn rents from providing liquidity. From the perspective of investment implications, outside investors can mimic the outperforming insiders and reap substantial portfolio returns that withstand the erosion from adjustments for both the standard factors and stock characteristics in the asset pricing literature.

The obligation to seek best execution on behalf of clients is not a new issue for investment advisers but one which has received increased scrutiny by the SEC's Office of Compliance Inspections and Examinations (OCIE). This article discusses an adviser's duty to seek best execution and offers suggested guidelines from regulators and industry advocates when developing and implementing best execution policies and procedures. It also illustrates different trading analyses and sample controls that advisers may wish to consider when establishing a best execution monitoring program.

The purpose of this paper is to review the context, rationale, execution strategies and results of the biggest property sale and leaseback programme Barclays has yet undertaken.

The paper is a review and analysis of Barclays' project documentation plus report and accounts, interviews with key decisionmakers, analysis of external economic and property market data in order to set the strategy choices and results achieved into context.

The sale and leaseback programme released capital and supported business objectives at a material level for Barclays; it achieved sales values that were at cyclical highs; flexibility in execution allowed additional value to be delivered across changing market conditions; a mixed skills team was critical for success.

The paper documents why the sale and leaseback programme made sense for the organisation and what elements were key to success both as a strategy and through execution. It provides a case study for how a large organisation approached a recent and large‐scale sale and leaseback opportunity across a portfolio of 900‐1,000 properties.

Stock markets during the day are relatively centralized, while night markets, due to the dominance of electronic trading venues, are fragmented. Though electronic markets at night allow more competition for order flow, they may result in decreased order interaction and decreased transparency. Using transaction data for three exchange traded funds (ETFs), we find that bid–ask spreads are wider at night due to higher order processing costs, market maker rents, and inventory holding costs. Results show that night markets are informationally fragmented and are not able to impound information available in net order flow to the same degree as day markets.