Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations

While the investors' responses to price changes and their price forecasts are well accepted major factors contributing to large price fluctuations in financial markets, our study shows that investors' heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in the dynamics of asset price fluctuations. We propose and study a model of an artificial stock market consisting of heterogeneous agents with DRA, and we find that DRA is the main driving force for excess price fluctuations and the associated volatility clustering. We employ a popular power utility function, $U(c,\gamma)=\frac{c^{1-\gamma}-1}{1-\gamma}$ with agent specific and time-dependent risk aversion index, $\gamma_i(t)$, and we derive an approximate formula for the demand function and aggregate price setting equation. The dynamics of each agent's risk aversion index, $\gamma_i(t)$ (i=1,2,...,N), is modeled by a bounded random walk with a constant variance $\delta^2$. We show numerically that our model reproduces most of the ``stylized'' facts observed in the real data, suggesting that dynamic risk aversion is a key mechanism for the emergence of these stylized facts.Comment: 17 pages, 7 figure

Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

Genomic Expansion of Magnetotactic Bacteria Reveals an Early Common Origin of Magnetotaxis with Lineage-specific Evolution

The origin and evolution of magnetoreception, which in diverse prokaryotes and protozoa is known as magnetotaxis and enables these microorganisms to detect Earth’s magnetic field for orientation and navigation, is not well understood in evolutionary biology. The only known prokaryotes capable of sensing the geomagnetic field are magnetotactic bacteria (MTB), motile microorganisms that biomineralize intracellular, membrane-bounded magnetic single-domain crystals of either magnetite (Fe3O4) or greigite (Fe3S4) called magnetosomes. Magnetosomes are responsible for magnetotaxis in MTB. Here we report the first large-scale metagenomic survey of MTB from both northern and southern hemispheres combined with 28 genomes from uncultivated MTB. These genomes expand greatly the coverage of MTB in the Proteobacteria, Nitrospirae, and Omnitrophica phyla, and provide the first genomic evidence of MTB belonging to the Zetaproteobacteria and “Candidatus Lambdaproteobacteria” classes. The gene content and organization of magnetosome gene clusters, which are physically grouped genes that encode proteins for magnetosome biosynthesis and organization, are more conserved within phylogenetically similar groups than between different taxonomic lineages. Moreover, the phylogenies of core magnetosome proteins form monophyletic clades. Together, these results suggest a common ancient origin of iron-based (Fe3O4 and Fe3S4) magnetotaxis in the domain Bacteria that underwent lineage-specific evolution, shedding new light on the origin and evolution of biomineralization and magnetotaxis, and expanding significantly the phylogenomic representation of MTB

A deeply branching thermophilic bacterium with an ancient acetyl-CoA pathway dominates a subsurface ecosystem

<div><p>A nearly complete genome sequence of <em>Candidatus</em> ‘Acetothermum autotrophicum’, a presently uncultivated bacterium in candidate division OP1, was revealed by metagenomic analysis of a subsurface thermophilic microbial mat community. Phylogenetic analysis based on the concatenated sequences of proteins common among 367 prokaryotes suggests that <em>Ca.</em> ‘A. autotrophicum’ is one of the earliest diverging bacterial lineages. It possesses a folate-dependent Wood-Ljungdahl (acetyl-CoA) pathway of CO₂ fixation, is predicted to have an acetogenic lifestyle, and possesses the newly discovered archaeal-autotrophic type of bifunctional fructose 1,6-bisphosphate aldolase/phosphatase. A phylogenetic analysis of the core gene cluster of the acethyl-CoA pathway, shared by acetogens, methanogens, some sulfur- and iron-reducers and dechlorinators, supports the hypothesis that the core gene cluster of <em>Ca.</em> ‘A. autotrophicum’ is a particularly ancient bacterial pathway. The habitat, physiology and phylogenetic position of <em>Ca.</em> ‘A. autotrophicum’ support the view that the first bacterial and archaeal lineages were H₂-dependent acetogens and methanogenes living in hydrothermal environments.</p> </div

Association of liver enzymes with incident type 2 diabetes: A nested case control study in an Iranian population

<p>Abstract</p> <p>Background</p> <p>To investigate the association of Aspartate aminotransferase (AST), Alanin aminotranferase (ALT) and Gamma glutamyl transferase (GGT) with incident type 2 diabetes.</p> <p>Methods</p> <p>In a nested case-control study, AST, ALT, GGT as well as classic diabetes risk factors, insulin and C-reactive protein (CRP) were measured in 133 non-diabetic subjects at baseline of which 68 were cases and 65 were controls. Incident diabetes was defined by the WHO 1999 criteria. Conditional logistic regression was used to calculate the odds ratio (OR) of incident diabetes associated with different hepatic markers. We used factor analysis for clustering of classic diabetes risk factors.</p> <p>Results</p> <p>In Univariate analysis both ALT and GGT were associated with diabetes with ORs of 3.07(1.21–7.79) and 2.91(1.29–6.53) respectively. After adjustment for CRP and insulin, ALT and GGT were still predictive of incident diabetes. When the model was further adjusted for anthropometric, blood pressure and metabolic factors, only ALT was independently associated with diabetes [OR = 3.18 (1.02–9.86)]. No difference was found between the area under the receiver operating characteristic curves of the models with and without ALT (0.820 and 0.802 respectively, P = 0.4)</p> <p>Conclusion</p> <p>ALT is associated with incident type 2 diabetes independent of classic risk factors. However, its addition to the classic risk factors does not improve the prediction of diabetes.</p

Use of hierarchical models to evaluate performance of cardiac surgery centres in the Italian CABG outcome study

<p>Abstract</p> <p>Background</p> <p>Hierarchical modelling represents a statistical method used to analyze nested data, as those concerning patients afferent to different hospitals. Aim of this paper is to build a hierarchical regression model using data from the "Italian CABG outcome study" in order to evaluate the amount of differences in adjusted mortality rates attributable to differences between centres.</p> <p>Methods</p> <p>The study population consists of all adult patients undergoing an isolated CABG between 2002–2004 in the 64 participating cardiac surgery centres.</p> <p>A risk adjustment model was developed using a classical single-level regression. In the multilevel approach, the variable "clinical-centre" was employed as a group-level identifier. The intraclass correlation coefficient was used to estimate the proportion of variability in mortality between groups. Group-level residuals were adopted to evaluate the effect of clinical centre on mortality and to compare hospitals performance. Spearman correlation coefficient of ranks (<it>ρ</it>) was used to compare results from classical and hierarchical model.</p> <p>Results</p> <p>The study population was made of 34,310 subjects (mortality rate = 2.61%; range 0.33–7.63). The multilevel model estimated that 10.1% of total variability in mortality was explained by differences between centres. The analysis of group-level residuals highlighted 3 centres (VS 8 in the classical methodology) with estimated mortality rates lower than the mean and 11 centres (VS 7) with rates significantly higher. Results from the two methodologies were comparable (<it>ρ </it>= 0.99).</p> <p>Conclusion</p> <p>Despite known individual risk-factors were accounted for in the single-level model, the high variability explained by the variable "clinical-centre" states its importance in predicting 30-day mortality after CABG.</p

Behavioral Finance

Behavioral finance studies the application of psychology to finance, with a focus on individual-level cognitive biases. I describe here the sources of judgment and decision biases, how they affect trading and market prices, the role of arbitrage and flows of wealth between more rational and less rational investors, how firms exploit inefficient prices and incite misvaluation, and the effects of managerial judgment biases. There is need for more theory and testing of the effects of feelings on financial decisions and aggregate outcomes. Especially, the time has come to move beyond behavioral finance to social finance, which studies the structure of social interactions, how financial ideas spread and evolve, and how social processes affect financial outcomes

Changing pattern in the basal ganglia: motor switching under reduced dopaminergic drive

Action selection in the basal ganglia is often described within the framework of a standard model, associating low dopaminergic drive with motor suppression. Whilst powerful, this model does not explain several clinical and experimental data, including varying therapeutic efficacy across movement disorders. We tested the predictions of this model in patients with Parkinson’s disease, on and off subthalamic deep brain stimulation (DBS), focussing on adaptive sensory-motor responses to a changing environment and maintenance of an action until it is no longer suitable. Surprisingly, we observed prolonged perseverance under on-stimulation, and high inter-individual variability in terms of the motor selections performed when comparing the two conditions. To account for these data, we revised the standard model exploring its space of parameters and associated motor functions and found that, depending on effective connectivity between external and internal parts of the globus pallidus and saliency of the sensory input, a low dopaminergic drive can result in increased, dysfunctional, motor switching, besides motor suppression. This new framework provides insight into the biophysical mechanisms underlying DBS, allowing a description in terms of alteration of the signal-to-baseline ratio in the indirect pathway, which better account of known electrophysiological data in comparison with the standard model

Expression and biological-clinical significance of hTR, hTERT and CKS2 in washing fluids of patients with bladder cancer

<p>Abstract</p> <p>Background</p> <p>at present, pathogenesis of bladder cancer (BC) has not been fully elucidated. Aim of this study is to investigate the role of human telomerase RNA (<it>hTR</it>), human telomerase reverse transcriptase (<it>hTERT</it>) and CDC28 protein kinase regulatory subunit 2 (<it>CKS2</it>) in bladder carcinogenesis and their possible clinical significance;</p> <p>Methods</p> <p>the transcript levels of <it>hTR</it>, <it>hTERT </it>and <it>CKS2 </it>were quantified by Real time reverse transcriptase chain reaction in exfoliated cells from bladder washings of 36 patients with BC and 58 controls. The statistical significance of differences between BC bearing patients and control groups, in the general as well as in the stratified analysis (superficial or invasive BC), was assessed by Student's t test. Non parametric Receiver Operating Characteristics analysis (ROC) was performed to ascertain the accuracy of study variables to discriminate between BC and controls. The clinical value of concomitant examination of <it>hTR</it>, <it>hTERT </it>and <it>CKS2 </it>was evaluated by logistic regression analysis;</p> <p>Results</p> <p>a significant decrease in <it>hTR </it>and a significant increase in <it>hTERT </it>or <it>CKS2 </it>gene expression were found between BC bearing patients and controls, as well as in the subgroups analysis. The area under the curve (AUC) indicated an average discrimination power for the three genes, both in the general and subgroups analysis, when singularly considered. The ability to significantly discriminate between superficial and invasive BC was observed only for <it>hTR </it>transcript levels. A combined model including <it>hTR </it>and <it>CKS2 </it>was the best one in BC diagnosis;</p> <p>Conclusions</p> <p>our results, obtained from a sample set particularly rich of exfoliated cells, provide further molecular evidence on the involvement of <it>hTR, hTERT </it>and <it>CKS2 </it>gene expression in BC carcinogenesis. In particular, while <it>hTERT </it>and <it>CKS2 </it>gene expression seems to have a major involvement in the early stages of the disease, <it>hTR </it>gene expression, seems to be more involved in progression. In addition, our findings suggest that the studied genes have a clinical role in discriminating between BC and controls in the general as well as in the stratified analysis, when singularly considered. A combined model improved over the single marker BC diagnosis.</p

Robust tests for time-invariant individual heterogeneity versus dynamic state dependence

We derive tests for persistent effects in a general linear dynamic panel data context. Two sources of persistent behavior are considered: time-invariant unobserved factors (captured by an individual random effect) and dynamic persistence or “state dependence” (captured by autoregressive behavior). We will use a maximum likelihood framework to derive a family of tests that help researchers learn whether persistence is due to individual heterogeneity, dynamic effect, or both. The proposed tests have power only in the direction they are designed to perform, that is, they are locally robust to the presence of alternative sources of persistence, and consequently, are able to identify which source of persistence is active. A Monte Carlo experiment is implemented to explore the finite sample performance of the proposed procedures. The tests are applied to a panel data series of real GDP growth for the period 1960–2005