An investigation of customer order flow in the foreign exchange market

This paper examines the effect that heterogeneous customer orders flows have on exchange rates by using a new, and the largest, proprietary dataset of weekly net order flow segmented by customer type across nine of the most liquid currency pairs. We make several contributions. Firstly, we investigate the extent to which customer order flow can help to explain exchange rate movements over and above the influence of macroeconomic variables. Secondly, we address the issue of whether order flows contain (private) information which explain exchange rates changes. Thirdly, we look at the usefulness of order flow in forecasting exchange rate movements at longer horizons than those generally considered in the microstructure literature. Finally we address the question of whether the out-of-sample exchange rate forecasts generated by order flows can be employed profitably in the foreign exchange markets

Transcriptional profiling of CD4 T cells identifies distinct subgroups of HIV-1 elite controllers.

Human immunodeficiency virus type 1 (HIV-1) elite controllers maintain undetectable levels of viral replication in the absence of antiretroviral therapy (ART), but their underlying immunological and virological characteristics may vary. Here, we used a whole-genome transcriptional profiling approach to characterize gene expression signatures of CD4 T cells from an unselected cohort of elite controllers. The transcriptional profiles for the majority of elite controllers were similar to those of ART-treated patients but different from those of HIV-1-negative persons. Yet, a smaller proportion of elite controllers showed an alternative gene expression pattern that was indistinguishable from that of HIV-1-negative persons but different from that of highly active antiretroviral therapy (HAART)-treated individuals. Elite controllers with the latter gene expression signature had significantly higher CD4 T cell counts and lower levels of HIV-1-specific CD8(+) T cell responses but did not significantly differ from other elite controllers in terms of HLA class I alleles, HIV-1 viral loads determined by ultrasensitive single-copy PCR assays, or chemokine receptor polymorphisms. Thus, these data identify a specific subgroup of elite controllers whose immunological and gene expression characteristics approximate those of HIV-1-negative persons.

Versatile gene-specific sequence tags for Arabidopsis functional genomics: transcript profiling and reverse genetics applications.

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.

Endogenous steroid profiling in the athlete biological passport.

The Athlete Biological Passport (ABP) is an individual electronic document that collects data regarding a specific athlete that is useful in differentiating between natural physiologic variations of selected biomarkers and deviations caused by artificial manipulations. A subsidiary of the endocrine module of the ABP, that which here is called Athlete Steroidal Passport (ASP), collects data on markers of an altered metabolism of endogenous steroidal hormones measured in urine samples. The ASP aims to identify not only doping with anabolic-androgenic steroids, but also most indirect steroid doping strategies such as doping with estrogen receptor antagonists and aromatase inhibitors. Development of specific markers of steroid doping, use of the athlete's previous measurements to define individual limits, with the athlete becoming his or her own reference, the inclusion of heterogeneous factors such as the UDPglucuronosyltransferase B17 genotype of the athlete, the knowledge of potentially confounding effects such as heavy alcohol consumption, the development of an external quality control system to control analytical uncertainty, and finally the use of Bayesian inferential methods to evaluate the value of indirect evidence have made the ASP a valuable alternative to deter steroid doping in elite sports. The ASP can be used to target athletes for gas chromatography/combustion/ isotope ratio mass spectrometry (GC/C/IRMS) testing, to withdraw temporarily the athlete from competing when an abnormality has been detected, and ultimately to lead to an antidoping infraction if that abnormality cannot be explained by a medical condition. Although the ASP has been developed primarily to ensure fairness in elite sports, its application in endocrinology for clinical purposes is straightforward in an evidence-based medicine paradigm.

Chemical profiling of different hashish seizures by gas chromatography-mass spectrometry and statistical methodology: a case report

Limited information is available regarding the methodology required to characterize hashish seizures for assessing the presence or the absence of a chemical link between two seizures. This casework report presents the methodology applied for assessing that two different police seizures were coming from the same block before this latter one was split. The chemical signature was extracted using GC-MS analysis and the implemented methodology consists in a study of intra- and inter-variability distributions based on the measurement of the chemical profiles similarity using a number of hashish seizures and the calculation of the Pearson correlation coefficient. Different statistical scenarios (i.e., a combination of data pretreatment techniques and selection of target compounds) were tested to find the most discriminating one. Seven compounds showing high discrimination capabilities were selected on which a specific statistical data pretreatment was applied. Based on the results, the statistical model built for comparing the hashish seizures leads to low error rates. Therefore, the implemented methodology is suitable for the chemical profiling of hashish seizures.

Transcriptional profiling reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver.

Little is known about the role of the transcription factor peroxisome proliferator-activated receptor (PPAR) beta/delta in liver. Here we set out to better elucidate the function of PPARbeta/delta in liver by comparing the effect of PPARalpha and PPARbeta/delta deletion using whole genome transcriptional profiling and analysis of plasma and liver metabolites. In fed state, the number of genes altered by PPARalpha and PPARbeta/delta deletion was similar, whereas in fasted state the effect of PPARalpha deletion was much more pronounced, consistent with the pattern of gene expression of PPARalpha and PPARbeta/delta. Minor overlap was found between PPARalpha- and PPARbeta/delta-dependent gene regulation in liver. Pathways upregulated by PPARbeta/delta deletion were connected to innate immunity and inflammation. Pathways downregulated by PPARbeta/delta deletion included lipoprotein metabolism and various pathways related to glucose utilization, which correlated with elevated plasma glucose and triglycerides and reduced plasma cholesterol in PPARbeta/delta-/- mice. Downregulated genes that may underlie these metabolic alterations included Pklr, Fbp1, Apoa4, Vldlr, Lipg, and Pcsk9, which may represent novel PPARbeta/delta target genes. In contrast to PPARalpha-/- mice, no changes in plasma free fatty acid, plasma beta-hydroxybutyrate, liver triglycerides, and liver glycogen were observed in PPARbeta/delta-/- mice. Our data indicate that PPARbeta/delta governs glucose utilization and lipoprotein metabolism and has an important anti-inflammatory role in liver. Overall, our analysis reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver.

A logistic regression approach to estimating customer profit loss due to lapses in insurance

This article focuses on business risk management in the insurance industry. A methodology for estimating the profit loss caused by each customer in the portfolio due to policy cancellation is proposed. Using data from a European insurance company, customer behaviour over time is analyzed in order to estimate the probability of policy cancelation and the resulting potential profit loss due to cancellation. Customers may have up to two different lines of business contracts: motor insurance and other diverse insurance (such as, home contents, life or accident insurance). Implications for understanding customer cancellation behaviour as the core of business risk management are outlined.

Illicit drug profiling, reflection on statistical comparisons

This paper presents reflexions about statistical considerations on illicit drug profiling and more specifically about the calculation of threshold for determining of the seizure are linked or not. The specific case of heroin and cocaine profiling is presented with the necessary details on the target profiling variables (major alkaloids) selected and the analytical method used. Statistical approach to compare illicit drug seizures is also presented with the introduction of different scenarios dealing with different data pre-treatment or transformation of variables.The main aim consists to demonstrate the influence of data pre-treatment on the statistical outputs. A thorough study of the evolution of the true positive rate (TP) and the false positive rate (FP) in heroin and cocaine comparison is then proposed to investigate this specific topic and to demonstrate that there is no universal approach available and that the calculations have to be revaluate for each new specific application.

Customer Service Action Plan

Customer Service Action Plan One of the fundamental themes of Delivering Better Government (1996) is the â?oachievement of an excellent service for the Government and for the public as customers and clients at all levelsâ?Âù. In 2000, the Quality Customer Service (QCS) Working Group reviewed and revised the 1997 Principles of Quality Customer Service to take account of changes in the environment since 1997, such as the equality agenda. In July 2000, the Government decided that: Click here to download PDF 199kb

Quality Customer Service Action Plan 2005 - 2007

Quality Customer Service Action Plan 2005 – 2007 Quality Customer Action Plan

Untargeted profiling of urinary steroid metabolites after testosterone ingestion: opening new perspectives for antidoping testing.

AIM: Antidoping procedures are expected to greatly benefit from untargeted metabolomic approaches through the discovery of new biomarkers of prohibited substances abuse. RESULTS: Endogenous steroid metabolites were monitored in urine samples from a controlled elimination study of testosterone undecanoate after ingestion. A platform coupling ultra-high pressure LC with high-resolution quadrupole TOF MS was used and high between-subject metabolic variability was successfully handled using a multiblock data analysis strategy. Links between specific subsets of metabolites and influential genetic polymorphisms of the UGT2B17 enzyme were highlighted. CONCLUSION: This exploratory metabolomic strategy constitutes a first step toward a better understanding of the underlying patterns driving the high interindividual variability of steroid metabolism. Promising biomarkers were selected for further targeted study.

The use of methylamphetamine chemical profiling in an intelligence-led perspective and the observation of inhomogeneity within seizures

This study focuses on methylamphetamine (MA) seizures made by the Australian Federal Police (AFP) to investigate the use of chemical profiling in an intelligence perspective. Correlation coefficients were used to obtain a similarity degree between a population of linked samples and a population of unlinked samples. Although it was demonstrated that a general framework can be followed for the use of any forensic case data in an intelligence-led perspective, threshold values have to be re-evaluated for each type of illicit drug investigated. Unlike the results obtained in a previous study on 3,4-methylenedioxymethylamphetamine (MDMA) seizures, chemical profiles of MA samples coming from the same seizure showed relative inhomogeneity, limiting their ability to link seizures. Different hypotheses were investigated to obtain a better understanding of this inhomogeneity although no trend was observed. These findings raise an interesting discussion in regards to the homogeneity and representativeness of illicit drug seizures (for intelligence purposes). Further, it also provides some grounds to discuss the initial hypotheses and assumptions that most forensic science studies are based on.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue.

Background: The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods: RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results: Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_ 5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_ 5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions: Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.