Assessing multivariate predictors of financial market movements: A latent factor framework for ordinal data

Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called "soft dollars," which basically are amounts spent in "research" for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD 10 paid in commissions. Obviously they are costly, and it is interesting for an institutional investor to determine whether soft dollar inputs are worth being used (and indirectly paid for) or not, from a statistical point of view. To address this question, we develop association measures between what broker--dealers predict and what markets realize. Our data are ordinal predictions by two broker--dealers and realized values on several markets, on the same ordinal scale. We develop a structural equation model with latent variables in an ordinal setting which allows us to test broker--dealer predictive ability of financial market movements. We use a multivariate logit model in a latent factor framework, develop a tractable estimator based on a Laplace approximation, and show its consistency and asymptotic normality. Monte Carlo experiments reveal that both the estimation method and the testing procedure perform well in small samples. The method is then used to analyze our dataset.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS213 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

[Endothelial cell-cell junctions in vessel formation.]

International audienceThe endothelium, lining the inner side of all vessel types, is constituted of a monolayer of endothelial cells with cobblestone morphology. Endothelial cell-cell contacts contain numerous transmembrane adhesive proteins that are either clustered in junctional structures or located along the intercellular cleft. These proteins promote cell-cell adhesion and control vascular permeability to fluids and molecules, as well as transmigration of various types of leukocytes. In addition, recent findings showed that constituents of the junctions might be part of the vascular invasion machinery by activating cell protrusions. Such activities may thus be considered as markers of pathological angiogenesis or targets of antiangiogenic therapy. L'endothélium, localisé sur la face interne de tous les types de vaisseaux, est constitué d'une monocouche pavimenteuse de cellules endothéliales. La zone de contact intercellulaire endothéliale contient plusieurs protéines transmembranaires à activité adhésive qui sont soit incluses dans des structures jonctionnelles spécifiques, soit localisées le long de la zone de contact. Ces protéines sont essentielles pour l'adhérence intercellulaire et le contrôle de la perméabilité vasculaire aux fluides, aux molécules et à la transmigration de plusieurs types de globules blancs. Récemment, il a été montré que certains constituants des jonctions pouvaient également être impliqués dans l'activité protrusive des cellules permettant l'invasion cellulaire. Ces propriétés peuvent donc être considérées comme des cibles pour des thérapies antiangiogéniques

On the Connectivity of Unions of Random Graphs

Graph-theoretic tools and techniques have seen wide use in the multi-agent systems literature, and the unpredictable nature of some multi-agent communications has been successfully modeled using random communication graphs. Across both network control and network optimization, a common assumption is that the union of agents' communication graphs is connected across any finite interval of some prescribed length, and some convergence results explicitly depend upon this length. Despite the prevalence of this assumption and the prevalence of random graphs in studying multi-agent systems, to the best of our knowledge, there has not been a study dedicated to determining how many random graphs must be in a union before it is connected. To address this point, this paper solves two related problems. The first bounds the number of random graphs required in a union before its expected algebraic connectivity exceeds the minimum needed for connectedness. The second bounds the probability that a union of random graphs is connected. The random graph model used is the Erd\H{o}s-R\'enyi model, and, in solving these problems, we also bound the expectation and variance of the algebraic connectivity of unions of such graphs. Numerical results for several use cases are given to supplement the theoretical developments made.Comment: 16 pages, 3 tables; accepted to 2017 IEEE Conference on Decision and Control (CDC

A latent factor model for ordinal data to measure multivariate predictive ability of financial market movements

In this paper we develop a structural equation model with latent variables in an ordinal setting which allows us to test broker-dealer predictive ability of financial market movements. We use a multivariate logit model in a latent factor framework, develop a tractable estimator based on a Laplace approximation, and show its consistency and asymptotic normality. Monte Carlo experiments reveal that both the estimation method and the testing procedure perform well in small samples. An empirical illustration is given for mid-term forecasts simultaneously made by two broker-dealers for several countries.structural equation model, latent variable, generalised linear model, factor analysis, multinomial logit, forecasts, LAMLE, canonical correlation

Angiogenesis: the VE-cadherin switch.

International audienceBecause angiogenesis is a key step in a number of pathologic processes, including tumor growth and atherosclerosis, many research studies have investigated the regulatory signals active at various stages of vascular invasion. The differential activities of the endothelial junction protein vascular endothelial (VE)-cadherin reflect the versatile behavior of endothelial cells between vascular quiescence and angiogenesis. VE-cadherin function and signaling are deeply modified in proliferating cells, and this conversion is accompanied by phosphorylation of the protein on tyrosine residues and enhanced transcription of its gene. Recent advances in the complex interplay between protein tyrosine kinases and phosphatases regulating VE-cadherin phosphorylation and function are discussed in this review

On the challenge of reconstructing level-1 phylogenetic networks from triplets and clusters

Phylogenetic networks have gained prominence over the years due to their ability to represent complex non-treelike evolutionary events such as recombination or hybridization. Popular combinatorial objects used to construct them are triplet systems and cluster systems, the motivation being that any network $N$ induces a triplet system $\mathcal R(N)$ and a softwired cluster system $\mathcal S(N)$. Since in real-world studies it cannot be guaranteed that all triplets/softwired clusters induced by a network are available, it is of particular interest to understand whether subsets of $\mathcal R(N)$ or $\mathcal S(N)$ allow one to uniquely reconstruct the underlying network $N$. Here we show that even within the highly restricted yet biologically interesting space of level-1 phylogenetic networks it is not always possible to uniquely reconstruct a level-1 network $N$\kelk{,} even when all triplets in $\mathcal R(N)$ or all clusters in $\mathcal S(N)$ are available. On the positive side, we introduce a reasonably large subclass of level-1 networks the members of which are uniquely determined by their induced triplet/softwired cluster systems. Along the way, we also establish various enumerative results, both positive and negative, including results which show that certain special subclasses of level-1 networks $N$ can be uniquely reconstructed from proper subsets of $\mathcal R(N)$ and $\mathcal S(N)$. We anticipate these results to be of use in the design of algorithms for phylogenetic network inference

Uprooted Phylogenetic Networks

The need for structures capable of accommodating complex evolutionary signals such as those found in, for example, wheat has fueled research into phylogenetic networks. Such structures generalize the standard model of a phylogenetic tree by also allowing for cycles and have been introduced in rooted and unrooted form. In contrast to phylogenetic trees or their unrooted versions, rooted phylogenetic networks are notoriously difficult to understand. To help alleviate this, recent work on them has also centered on their “uprooted” versions. By focusing on such graphs and the combinatorial concept of a split system which underpins an unrooted phylogenetic network, we show that not only can a so-called (uprooted) 1-nested network N be obtained from the Buneman graph (sometimes also called a median network) associated with the split system  Σ(N)Σ(N)  induced on the set of leaves of N but also that that graph is, in a well-defined sense, optimal. Along the way, we establish the 1-nested analogue of the fundamental “splits equivalence theorem” for phylogenetic trees and characterize maximal circular split systems

Tracing the glycogen cells with protocadherin 12 during mouse placenta development.

International audienceAmong the different trophoblast subtypes of the mouse placenta, the glycogen cells (GC) are one of the trophoblast subtypes that invade the decidua. We previously established that GC specifically expressed protocadherin 12 (PCDH12). In this paper, we investigated the origin of the PCDH12-positive cells and we characterized their fate in the maternal tissues. Our data indicate that they directly originate from the central part of the ectoplacental cone at embryonic day (E) 7.5. PCDH12-positive cells start to accumulate glycogen from E10.5 and the first migrating cells could be observed from this age. Unlike other placental and decidual cells, GC do not express P-cadherin, which may explain their migration properties in this organ. In the decidua, GC settle in the vicinity of the maternal vascular sinuses but do not incorporate in the endothelium. By the end of gestation (E17.5), most GC islets of the decidua enter into a lytic phase and form large lacunae. These lacunae, filled with glycogen, may provide a substantial source of energy at the end of gestation or during delivery. Our data suggest that spongiotrophoblasts and GC are two independent lineages and we bring insights into GC migration and fate