The Role of Supervised Learning in the Decision Process to Fair Trade US Municipal Debt

Determining a fair price and an appropriate timescale to trade municipal debt is a complex decision. This research uses data informatics to explore transaction characteristics and trading activity of investment grade US municipal bonds. Using the relatively recent data stream distributed by the Municipal Securities Rulemaking Board, we provide an institutional summary of market participants and their trading behavior. Subsequently, we focus on a sample of AAA bonds to derive a new methodology to estimate a trade-weighted benchmark municipal yield curve. The methodology integrates the study of ridge regression, artificial neural networks, and support vector regression. We find an enhanced radial basis function artificial neural network outperforms alternate methods used to estimate municipal term structure. This result forms the foundation for establishing a decision theory on optimal municipal bond trading. Using multivariate modeling of a liquidity domain measured across three dependent variables, we investigate the proposed decision theory by estimating weekly production-theoretic bond liquidity returns to scale. Across the three liquidity measures and for almost all weeks investigated, bond trading liquidity is elastic with respect to the modeled factors. This finding leads us to conclude that an optimal trading policy for municipal debt can be implemented on a weekly timescale using the elasticity estimates of bond price, trade size, risk, days-to-maturity, and the macroeconomic influences of labor in the workforce and building activity

Blood group antigens and integrins as biomarkers in head and neck cancer: Is aberrant tyrosine phosphorylation the cause of altered Α6Β4 integrin expression?

Head and neck cancer is a capricious disease that varies greatly in its clinical behavior. The development of biomarkers that can distinguish between biologically aggressive and indolent tumors has been a long term goal of our laboratories. Predictive markers applicable to biopsy specimens should facilitate clinical management through early identification of patients at greatest risk for early relapse or metastatic spread. Two prominent cell surface markers that we identified by raising monoclonal antibodies to squamous cell carcinomas are blood group antigens and the A9 antigen/Α6Β4 integrin. Both of these markers are abnormally displayed in squamous cancers of the head and neck and serve as indicators of early relapse. Loss of blood group antigen expression is a stronger single indicator than is overexpression of the Α6Β4 integrin. However, use of both markers together is a stronger predictive indicator than is either alone. We know little about the function of the blood group antigens in squamous cells except that the mature antigens are associated with differentiation. Similarly, the function of the Α6Β4 integrin is also not fully understood. Integrin Α6Β4 is thought to serve as an extracellular matrix receptor, but its ligand has not been confirmed. In resting epithelium, the Α6Β4 integrin is polarized to the basal aspect of the basal cell as a component of the hemidesmosome, the anchoring structures of the epithelia. This basal polarization is lost in migrating normal squamous cells and squamous carcinomas. Tyrosine phosphorylation of the Β4 subunit is absent or greatly reduced in malignant cells and this may be a critical signal for subcellular localization of Α6Β4 and cell anchoring. On the basis of our current experimental results, we postulate that tyrosine phosphorylation of the Β4 subunit is a reversible signal that regulates cell migration in normal and malignant cells, and may therefore be an important initial event in the metastatic cascade.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38454/1/240531033_ftp.pd

The acridonecarboxamide GF120918 potently reverses P-glycoprotein-mediated resistance in human sarcoma MES-Dx5 cells

The doxorubicin-selected, P-glycoprotein (P-gp)-expressing human sarcoma cell line MES-Dx5 showed the following levels of resistance relative to the non-P-gp-expressing parental MES-SA cells in a 72 h exposure to cytotoxic drugs: etoposide twofold, doxorubicin ninefold, vinblastine tenfold, taxotere 19-fold and taxol 94-fold. GF120918 potently reversed resistance completely for all drugs. The EC50s of GF120918 to reverse resistance of MES-Dx5 cells were: etoposide 7 ± 2 nM, vinblastine 19 ± 3 nM, doxorubicin 21 ± 6 nM, taxotere 57 ± 14 nM and taxol 91 ± 23 nM. MES-Dx5 cells exhibited an accumulation deficit relative to the parental MES-SA cells of 35% for [3H]-vinblastine, 20% for [3H]-taxol and [14C]-doxorubicin. The EC50 of GF120918, to reverse the accumulation deficit in MES-Dx5 cells, ranged from 37 to 64 nM for all three radiolabelled cytotoxics. [3H]-vinblastine bound saturably to membranes from MES-Dx5 cells with a KD of 7.8 ± 1.4 nM and a Bmax of 5.2 ± 1.6 pmol mg–1 protein. Binding of [3H]-vinblastine to P-gp in MES-Dx5 membranes was inhibited by GF120918 (Ki = 5 ± 1 nM), verapamil (Ki = 660 ± 350 nM) and doxorubicin (Ki = 6940 ± 2100 nM). Taxol, an allosteric inhibitor of [3H]-vinblastine binding to P-gp, could only displace 40% of [3H]-vinblastine (Ki = 400 ± 140 nM). The novel acridonecarboxamide derivative GF120918 potently overcomes P-gp-mediated multidrug resistance in the human sarcoma cell line MES-Dx5. Detailed analysis revealed that five times higher GF120918 concentrations were needed to reverse drug resistance to taxol in the cytotoxicity assay compared to doxorubicin, vinblastine and etoposide. An explanation for this phenomenon had not been found. © 1999 Cancer Research Campaig

The topography of transmembrane segment six is altered during the catalytic cycle of P-glycoprotein

Structural evidence has demonstrated that P-glycoprotein (P-gp) undergoes considerable conformational changes during catalysis, and these alterations are important in drug interaction. Knowledge of which regions in P-gp undergo conformational alterations will provide vital information to elucidate the locations of drug binding sites and the mechanism of coupling. A number of investigations have implicated transmembrane segment six (TM6) in drug-P-gp interactions, and a cysteine-scanning mutagenesis approach was directed to this segment. Introduction of cysteine residues into TM6 did not disturb basal or drug-stimulated ATPase activity per se. Under basal conditions the hydrophobic probe coumarin maleimide readily labeled all introduced cysteine residues, whereas the hydrophilic fluorescein maleimide only labeled residue Cys-343. The amphiphilic BODIPY-maleimide displayed a more complex labeling profile. The extent of labeling with coumarin maleimide did not vary during the catalytic cycle, whereas fluorescein maleimide labeling of F343C was lost after nucleotide binding or hydrolysis. BODIPY-maleimide labeling was markedly altered during the catalytic cycle and indicated that the adenosine 5'-(beta,gamma-imino)triphosphate-bound and ADP/vanadate-trapped intermediates were conformationally distinct. Our data are reconciled with a recent atomic scale model of P-gp and are consistent with a tilting of TM6 in response to nucleotide binding and ATP hydrolysis

Cell Adhesion Molecules, Leukocyte Trafficking, and Strategies to Reduce Leukocyte Infiltration

Leukocyte-endothelial cell interactions are mediated by various cell adhesion molecules. These interactions are important for leukocyte extravasation and trafficking in all domestic animal species. An initial slowing of leukocytes on the vascular endothelium is mediated by selectins. This event is followed by (1) activation of β2 integrins after leukocyte exposure to cytokines and proinflammatory mediators, (2) adherence of leukocyte β2 integrins to vascular endothelial ligands (eg, intercellular adhesion molecule-1 [ICAM-1]), (3) extravasation of leukocytes into tissues through tight junctions of endothelial cells mediated by platelet and endothelial cell adhesion molecule-1 (PECAM-1), and (4) perivascular migration through the extracellular matrix via β1 integrins. Inhibiting excessive leukocyte egress and subsequent free radical-mediated damage caused by leukocyte components may attenuate or eliminate tissue damage. Several methods have been used to modify leukocyte infiltration in various animal models. These methods include nonspecific inhibition of pro-inflammatory mediators and adhesion molecules by nonsteroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids, inhibition of cytokines and cytokine receptors, and inhibition of specific types of cell adhesion molecules, with inhibitors such as peptides and antibodies to β2integrins, and inhibitors of selectins, ICAMs, and vascular cell adhesion molecule-1 (VCAM-1). By understanding the cellular and molecular events in leukocyte-endothelial cell interactions, therapeutic strategies are being developed in several animal models and diseases in domestic animal species. Such therapies may have clinical benefit in the future to overcome tissue damage induced by excessive leukocyte infiltration

Combinatorial nonlinear goal programming for ESG portfolio optimization and dynamic hedge management

Compared to their fundamentally weighted counterparts naively diversified investment portfolios that embrace environmental, sustainability and governance (ESG) factors are known to experience enhanced long-term investment performance. This paper introduces a combinatorial nonlinear multiple objective optimization model to diversify the short-term ESG portfolio. The expectation of long-term wealth creation from an ESG portfolio is also examined. This latter investment objective is explored by implementing a discrete period ESG portfolio re-balancing with attached dynamic hedging. Post simulation, we report comparatively higher Sharpe ratios and lower VaR metrics for the multiobjective and dynamically hedged ESG portfolio investment style

Computational practice: Multivariate parametric or nonparametric modelling of european bond volatility spillover?

Previous research has documented the effectiveness of multivariate nonparametric radial basis function artificial neural networks to model the simultaneous bi-directional volatility spillover effects among European economies. As a nonparametric estimation method, artificial neural networks do not present researchers with the same confidence levels on weight estimation that are commonplace under the assumption of asymptotic normality under linear regression. This chapter considers extending prior research findings by examining the domain of applicability for linear multivariate parametric model when applied to the estimation of global government bond volatility spillover models. To this end the chapter examines both multivariate linear regression and canonical correlation techniques to establish a comparative set of findings to those presented from prior research using a multivariate radial basis function artificial neural network. The findings clearly demonstrate that linear parametric methods fail to adequately explain the correlation and cross-correlation structure of excess European bond returns. Further, for studies designed to map the continuity of cross-border bond volatility spillover, the research demonstrates the overall effectiveness of neural networks to map such real-valued measurable functions. © 2013 by Nova Science Publishers, Inc. All rights reserved

On multiobjective combinatorial optimization and dynamic interim hedging of efficient portfolios

A dynamic portfolio policy is one that periodically rebalances an optimally diversified portfolio to account for time-varying correlations. In order to sustain target-level Sharpe performance ratios between rebalancing points, the efficient portfolio must be hedged with an optimal number of contingent claim contracts. This research presents a mixed-integer nonlinear goal program (MINLGP) that is directed to solve the hierarchical multiple goal portfolio optimization model when the decision maker is faced with a binary hedging decision between portfolio rebalance periods. The MINLGP applied to this problem is formed by extending the separable programming foundation of a lexicographic nonlinear goal program (NLGP) to include branch-and-bound constraints. We establish the economic efficiency of applying this normative approach to dynamic portfolio rebalancing by comparing the risk-adjusted performance measures of a hedged optimal portfolio to those of a naively diversified portfolio. We find that a hedged equally weighted small portfolio and a hedged efficiently diversified small portfolio perform similarly when comparing risk-adjusted return metrics. However, when percentile risk measures are used to measure performance, the hedged optimally diversified portfolio clearly produces less expected catastrophic loss than does its nonhedged and naively diversified counterpart