Random Matrix Theory Analysis of Cross Correlations in Financial Markets

We confirm universal behaviors such as eigenvalue distribution and spacings predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been reported for New York Stock Exchange in previous studies. It is shown that the random part of the eigenvalue distribution of the cross correlation matrix is stable even when deterministic correlations are present. Some deviations in the small eigenvalue statistics outside the bounds of the universality class of RMT are not completely explained with the deterministic correlations as proposed in previous studies. We study the effect of randomness on deterministic correlations and find that randomness causes a repulsion between deterministic eigenvalues and the random eigenvalues. This is interpreted as a reminiscent of ``level repulsion'' in RMT and explains some deviations from the previous studies observed in the market data. We also study correlated groups of issues in these markets and propose a refined method to identify correlated groups based on RMT. Some characteristic differences between properties of Tokyo Stock Exchange and New York Stock Exchange are found.Comment: RevTex, 17 pages, 8 figure

U.S. stock market interaction network as learned by the Boltzmann Machine

We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented analysis shows that binarization preserves market correlation structure. Properties of distributions of external fields and couplings as well as industry sector clustering structure are studied for different historical dates and moving window sizes. We found that a heavy positive tail in the distribution of couplings is responsible for the sparse market clustering structure. We also show that discrepancies between the model parameters might be used as a precursor of financial instabilities.Comment: 15 pages, 17 figures, 1 tabl

Statistical Properties of Cross-Correlation in the Korean Stock Market

We investigate the statistical properties of the correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The $\beta_{473}$ coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function $E(\sigma)$ with the portfolio risk $\sigma$ for the original and filtered correlation matrices are consistent with a power-law function, $E(\sigma) \sim \sigma^{-\gamma}$, with the exponent $\gamma \sim 2.92$ and those for Asian currency crisis decreases significantly

Factor analysis for gene regulatory networks and transcription factor activity profiles

BACKGROUND: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription factors (TFs) are proportional to their mRNA levels. This assumption is invalid for most biological systems. However, one might be able to reconstruct unobserved activity profiles of TFs from the expression profiles of target genes. A simple model is a two-layer network with unobserved TF variables in the first layer and observed gene expression variables in the second layer. TFs are connected to regulated genes by weighted edges. The weights, known as factor loadings, indicate the strength and direction of regulation. Of particular interest are methods that produce sparse networks, networks with few edges, since it is known that most genes are regulated by only a small number of TFs, and most TFs regulate only a small number of genes. RESULTS: In this paper, we explore the performance of five factor analysis algorithms, Bayesian as well as classical, on problems with biological context using both simulated and real data. Factor analysis (FA) models are used in order to describe a larger number of observed variables by a smaller number of unobserved variables, the factors, whereby all correlation between observed variables is explained by common factors. Bayesian FA methods allow one to infer sparse networks by enforcing sparsity through priors. In contrast, in the classical FA, matrix rotation methods are used to enforce sparsity and thus to increase the interpretability of the inferred factor loadings matrix. However, we also show that Bayesian FA models that do not impose sparsity through the priors can still be used for the reconstruction of a gene regulatory network if applied in conjunction with matrix rotation methods. Finally, we show the added advantage of merging the information derived from all algorithms in order to obtain a combined result. CONCLUSION: Most of the algorithms tested are successful in reconstructing the connectivity structure as well as the TF profiles. Moreover, we demonstrate that if the underlying network is sparse it is still possible to reconstruct hidden activity profiles of TFs to some degree without prior connectivity information

Enhanced Membrane Pore Formation through High-Affinity Targeted Antimicrobial Peptides

Many cationic antimicrobial peptides (AMPs) target the unique lipid composition of the prokaryotic cell membrane. However, the micromolar activities common for these peptides are considered weak in comparison to nisin, which follows a targeted, pore-forming mode of action. Here we show that AMPs can be modified with a high-affinity targeting module, which enables membrane permeabilization at low concentration. Magainin 2 and a truncated peptide analog were conjugated to vancomycin using click chemistry, and could be directed towards specific membrane embedded receptors both in model membrane systems and whole cells. Compared with untargeted vesicles, a gain in permeabilization efficacy of two orders of magnitude was reached with large unilamellar vesicles that included lipid II, the target of vancomycin. The truncated vancomycin-peptide conjugate showed an increased activity against vancomycin resistant Enterococci, whereas the full-length conjugate was more active against a targeted eukaryotic cell model: lipid II containing erythrocytes. This study highlights that AMPs can be made more selective and more potent against biological membranes that contain structures that can be targeted

Observation of Multi-Tev Diffuse Gamma Rays from the Galactic Plane with the Tibet Air Shower Array

Data from the Tibet-III air shower array (with energies around 3 TeV) and from the Tibet-II array (with energies around 10 TeV) have been searched for diffuse gamma rays from the Galactic plane. These arrays have an angular resolution of about 0.9 degrees. The sky regions searched are the inner Galaxy, 20 degrees <= l <= 55 degrees, and outer Galaxy, 140 degrees <= l <= 225 degrees, and |b| <= 2 degrees or <= 5 degrees. No significant Galactic plane gamma-ray excess was observed. The 99% confidence level upper limits for gamma-ray intensity obtained are (for |b| <= 2 degrees) 1.1 times 10^{-15} cm^{-2}s^{-1}sr^{-1}MeV^{-1} at 3 TeV and 4.1 times 10^{-17} cm^{-2}s^{-1}sr^{-1}MeV^{-1} at 10 TeV for the inner Galaxy, and 3.6 times 10^{-16} cm^{-2}s^{-1}sr^{-1}MeV^{-1} at 3 TeV and 1.3 times 10^{-17} cm^{-2}s^{-1}sr^{-1}MeV^{-1} at 10 TeV for the outer Galaxy, assuming a differential spectral index of 2.4. The upper limits are significant in the multi-TeV region when compared to those from Cherenkov telescopes in the lower energy region and other air shower arrays in the higher energy region; however, the results are not sufficient to rule out the inverse Compton model with a source electron spectral index of 2.0.Comment: 22 pages, 8 figures, Accepted for publication in Ap

The functional "KL-VS" variant of KLOTHO is not associated with type 2 diabetes in 5028 UK Caucasians

BACKGROUND: Klotho has an important role in insulin signalling and the development of ageing-like phenotypes in mice. The common functional "KL-VS" variant in the KLOTHO (KL) gene is associated with longevity in humans but its role in type 2 diabetes is not known. We performed a large case-control and family-based study to test the hypothesis that KL-VS is associated with type 2 diabetes in a UK Caucasian population. METHODS: We genotyped 1793 cases, 1619 controls and 1616 subjects from 509 families for the single nucleotide polymorphism (SNP) F352V (rs9536314) that defines the KL-VS variant. Allele and genotype frequencies were compared between cases and controls. Family-based analysis was used to test for over- or under-transmission of V352 to affected offspring. RESULTS: Despite good power to detect odds ratios of 1.2, there were no significant associations between alleles or genotypes and type 2 diabetes (V352 allele: odds ratio = 0.96 (0.84–1.09)). Additional analysis of quantitative trait data in 1177 healthy control subjects showed no association of the variant with fasting insulin, glucose, triglycerides, HDL- or LDL-cholesterol (all P > 0.05). However, the HDL-cholesterol levels observed across the genotype groups showed a similar, but non-significant, pattern to previously reported data. CONCLUSION: This is the first large-scale study to examine the association between common functional variation in KL and type 2 diabetes risk. We have found no evidence that the functional KL-VS variant is a risk factor for type 2 diabetes in a large UK Caucasian case-control and family-based study

Oxidized LDL Receptor 1 (OLR1) as a Possible Link between Obesity, Dyslipidemia and Cancer

Recent studies have linked expression of lectin-like ox-LDL receptor 1 (OLR1) to tumorigenesis. We analyzed microarray data from Olr1 knockout (KO) and wild type (WT) mice for genes involved in cellular transformation and evaluated effects of OLR1 over-expression in normal mammary epithelial cells (MCF10A) and breast cancer cells (HCC1143) in terms of gene expression, migration, adhesion and transendothelial migration. Twenty-six out of 238 genes were inhibited in tissues of OLR1 KO mice; the vast majority of OLR1 sensitive genes contained NF-κB binding sites in their promoters. Further studies revealed broad inhibition of NF-kB target genes outside of the transformation-associated gene pool, with enrichment themes of defense response, immune response, apoptosis, proliferation, and wound healing. Transcriptome of Olr1 KO mice also revealed inhibition of de novo lipogenesis, rate-limiting enzymes fatty acid synthase (Fasn), stearoyl-CoA desaturase (Scd1) and ELOVL family member 6 (Elovl6), as well as lipolytic phospholipase A2 group IVB (Pla2g4b). In studies comparing MCF10A and HCC1143, the latter displayed 60% higher OLR1 expression. Forced over-expression of OLR1 resulted in upregulation of NF-κB (p65) and its target pro-oncogenes involved in inhibition of apoptosis (BCL2, BCL2A1, TNFAIP3) and regulation of cell cycle (CCND2) in both cell lines. Basal expression of FASN, SCD1 and PLA2G4B, as well as lipogenesis transcription factors PPARA, SREBF2 and CREM, was higher in HCC1143 cells. Over-expression of OLR1 in HCC1143 cells also enhanced cell migration, without affecting their adherence to TNFα-activated endothelium or transendothelial migration. On the other hand, OLR1 neutralizing antibody inhibited both adhesion and transmigration of untreated HCC1143 cells. We conclude that OLR1 may act as an oncogene by activation of NF-kB target genes responsible for proliferation, migration and inhibition of apoptosis and de novo lipogenesis genes

Mifamurtide for the treatment of nonmetastatic osteosarcoma

International audienceINTRODUCTION: The standard treatment for osteosarcoma requires both macroscopic surgical wide resection and postoperative multi-drug chemotherapy in neoadjuvant and adjuvant settings. However, the 5-year event-free survival has remained at a plateau of 60-70% of patients with nonmetastatic osteosarcoma for more than 30 years. AREAS COVERED: Mifamurtide (liposomal muramyl tripeptide phosphatidylethanolamine; L-MTP-PE) is a new agent. L-MTP-PE is a nonspecific immunomodulator, which is a synthetic analog of a component of bacterial cell walls. L-MTP-PE activates macrophages and monocytes as a potent activator of immune response in addition to standard chemotherapy. It also improves the overall survival from 70 to 78% and results in a one-third reduction in the risk of death from osteosarcoma. This review summarizes the most recent findings about L-MTP-PE and its therapeutic application for nonmetastatic osteosarcoma. EXPERT OPINION: Recently, L-MTP-PE has been approved in Europe for the treatment of nonmetastatic osteosarcoma with chemotherapy. L-MTP-PE in combination with traditional treatment is expected to go mainstream and to be beneficial for patients with osteosarcoma. Information about potential benefit regarding mifamurtide use in the neoadjuvant setting (i.e., before surgery) and/or usefulness of L-MTP-PE in metastatic in relapsed and metastatic osteosarcoma requires analysis of expanded access and/or future clinical trials of L-MTP-PE in high-burden and low-burden situations

Induction of reactive oxygen intermediates in human monocytes by tumour cells and their role in spontaneous monocyte cytotoxicity

The present study examined the ability of human monocytes to produce reactive oxygen intermediates after a contact with tumour cells. Monocytes generated oxygen radicals, as measured by luminol-enhanced chemiluminescence and superoxide anion production, after stimulation with the tumour, but not with untransformed, cells. The use of specific oxygen radical scavengers and inhibitors, superoxide dismutase, catalase, dimethyl sulphoxide and deferoxamine as well as the myeloperoxidase inhibitor 4-aminobenzoic acid hydrazide, indicated that chemiluminescence was dependent on the production of superoxide anion and hydroxyl radical and the presence of myeloperoxidase. The tumour cell-induced chemiluminescent response of monocytes showed different kinetics from that seen after activation of monocytes with phorbol ester. These results indicate that human monocytes can be directly stimulated by tumour cells for reactive oxygen intermediate production. Spontaneous monocyte-mediated cytotoxicity towards cancer cells was inhibited by superoxide dismutase, catalase, deferoxamine and hydrazide, implicating the role of superoxide anion, hydrogen peroxide, hydroxyl radical and hypohalite. We wish to suggest that so-called ‘spontaneous’ tumoricidal capacity of freshly isolated human monocytes may in fact be an inducible event associated with generation of reactive oxygen intermediates and perhaps other toxic mediators, resulting from a contact of monocytes with tumour cells. © 1999 Cancer Research Campaig