Stability of cascade networks via fluid models

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Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Progression rate of self-propelled feeding tubes in critically ill patients.

OBJECTIVE: Gaining postpyloric access in ventilated, sedated ICU patients usually requires time-consuming procedures such as endoscopy. Recently, a feeding tube has been introduced that migrates spontaneously into the jejunum in surgical patients. The study aimed at assessing the rate of migration of this tube in critically ill patients. DESIGN: Prospective descriptive trial. SETTING: Surgical ICU in a tertiary University Hospital. PATIENTS: One hundred and five consecutive surgical ICU patients requiring enteral feeding were enrolled, resulting in 128 feeding-tube placement attempts. METHODS: A self-propelled tube was used and followed up for 3 days: progression was assessed by daily contrast-injected X-ray. Severity of illness was assessed with SAPS II and organ failure assessed with SOFA score. RESULTS: The patients were aged 55+/-19 years (mean+/-SD) with SAPS II score of 45+/-18. Of the 128 tube placement attempts, 12 could not be placed in the stomach; eight were accidentally pulled out while in gastric position due to the necessity to avoid fixation during the progression phase. Among organ failures, respiratory failure predominated, followed by cardiovascular. By day 3, the postpyloric progression rate was 63/128 tubes (49%). There was no association between migration and age, or SAPS II score, but the progression rate was significantly poorer in patients with hemodynamic failure. Use of norepinephrine and morphine were negatively associated with tube progression (P<0.001), while abdominal surgery was not. In ten patients, jejunal tubes were placed by endoscopy. CONCLUSION: Self-propelled feeding tubes progressed from the stomach to the postpyloric position in 49% of patients, reducing the number of endoscopic placements: these tubes may facilitate enteral nutrient delivery in the ICU.

Construcción y validación del cuestionario G_Clinic para medir la satisfacción laboral en profesionales de enfermería de las unidades de gestión clínica.

BACKGROUND Job satisfaction of nurses is a determinant factor in the quality and organizational adaptation of clinical management models in the current socio-economic context. The aim of this study was to construct and validate a questionnaire to measure job satisfaction of nurses in the Clinical Management Units in the Andalusian Public Health System. METHODS Clinimetric and cross-sectional study with a sample of 314 nurses of two university hospitals from Seville. Nurses were surveyed in 2011, from March to June. We used the Font Roja questionnaire adapted to our study variables. We performed analyses of correlations, reliability and construct validity, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to test the a priori model. RESULTS The end questionnaire consists of 10 items, whose internal consistency was 0.75, with a percentage of variance explaining of 63.67%. CFA confirmed 4 dimensions (work environment, work relationships, motivation, and recognition): significant χ2 (p < .001); χ2/gl = 2.013; GFI= 0.958, RMR = 0.055 y RMSEA = 0.057; AGFI = 0.927, NFI = 0.878, TLI = 0.902, CFI =0.933 e IFI = 0.935; AIC = 132.486 y ECVI = 0.423. CONCLUSION This new questionnaire (G_Clinic) improves clinimetric values of the Font Roja questionnaire, because it reduces the number of items, improves the reliability of the dimensions, increases the value of variance explained, and allows knowing job satisfaction of nurses in clinical managementt.

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution.

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a "covarion-like" pattern of correlated changes in evolutionary rates, and switches in conserved residues ("conserved but different"). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than "constant but different," but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.

Reaching for the Holy Grail: insights from infection/cure models on the prospects for vaccines for Trypanosoma cruziinfection

Prevention of Trypanosoma cruzi infection in mammals likely depends on either prevention of the invading trypomastigotes from infecting host cells or the rapid recognition and killing of the newly infected cells byT. cruzi-specific T cells. We show here that multiple rounds of infection and cure (by drug therapy) fails to protect mice from reinfection, despite the generation of potent T cell responses. This disappointing result is similar to that obtained with many other vaccine protocols used in attempts to protect animals from T. cruziinfection. We have previously shown that immune recognition ofT. cruziinfection is significantly delayed both at the systemic level and at the level of the infected host cell. The systemic delay appears to be the result of a stealth infection process that fails to trigger substantial innate recognition mechanisms while the delay at the cellular level is related to the immunodominance of highly variable gene family proteins, in particular those of the trans-sialidase family. Here we discuss how these previous studies and the new findings herein impact our thoughts on the potential of prophylactic vaccination to serve a productive role in the prevention of T. cruziinfection and Chagas disease.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

What makes articles highly cited?

We examined drivers of article citations using 776 articles that were published from 1990-2012 in a broad-based and high-impact social sciences journal, The Leadership Quarterly. These articles had 1,191 unique authors having published and received in total (at the time of their most recent article published in our dataset) 16,817 articles and 284,777 citations, respectively. Our models explained 66.6% of the variance in citations and showed that quantitative, review, method, and theory articles were significantly more cited than were qualitative articles or agent-based simulations. As concerns quantitative articles, which constituted the majority of the sample, our model explained 80.3% of the variance in citations; some methods (e.g., use of SEM) and designs (e.g., meta-analysis), as well as theoretical approaches (e.g., use of transformational, charismatic, or visionary type-leadership theories) predicted higher article citations. Regarding the statistical conclusion validity of quantitative articles, articles having endogeneity threats received significantly fewer citations than did those using a more robust design or an estimation procedure that ensured correct causal estimation. We make several general recommendations on how to improve research practice and article citations.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

The administration of atomoxetine during alcohol deprivation induces a time-limited increase in alcohol consumption after relapse.

The administration of selective serotonin reuptake inhibitors (SSRIs) typically used as antidepressants increases alcohol consumption after an alcohol deprivation period in rats. However, the appearance of this effect after the treatment with selective noradrenaline reuptake inhibitors (SNRIs) has not been studied. In the present work we examined the effects of a 15-d treatment with the SNRI atomoxetine (1, 3 and 10 mg/kg, i.p.) in male rats trained to drink alcohol solutions in a 4-bottle choice test. The treatment with atomoxetine (10 mg/kg, i.p.) during an alcohol deprivation period increased alcohol consumption after relapse. This effect only lasted one week, disappearing thereafter. Treatment with atomoxetine did not cause a behavioral sensitized response to a challenge dose of amphetamine (1.5 mg/kg, i.p.), indicating the absence of a supersensitive dopaminergic transmission. This effect is markedly different from that of SSRI antidepressants that produced both long-lasting increases in alcohol consumption and behavioral sensitization. Clinical implications are discussed.

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

Role of Age and Sex in the Diagnosis of Early-stage Malignant Melanoma: A Cross-Sectional study.

Age and sex have been identified as predictors of outcome in malignant melanoma (MM). This aim of this multicentre, cross-sectional study was to analyse the role of age and sex as explanatory variables for the diagnosis of thin MM. A total of 2430 patients with MM were recruited. Cases of in situ-T1 MM were more frequent than T2-T4 MM (56.26% vs. 43.74%). Breslow thickness increased throughout decades of life (analysis of variance (ANOVA) p < 0.001), with a weak correlation between Breslow thickness and patient's age (r   = 0.202, p < 0.001). Breslow thickness was significantly less in women (1.79 vs. 2.38 mm, p = 0.0001). Binary logistic regression showed a significant (p < 0.001) odds ratio for age 0-29 years (1.18), and 30-59 years (1.16), and for women (1.09). Age and sex explained 3.64% of the variation observed in Tis-T1 frequency (R2 = 0.0364). Age and sex appear to explain a low percentage of the variation in the early detection of MM.