Investment Dynamics with Natural Expectations

We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility.Economic

The Design and Validation of a UAV Propeller Intended for Extremely Low Reynolds Number Environments

Mars exploration and UAV development have both advanced significantly over the past century, and are now being considered in tandem. Currently needed are UAV propellers that can operate in the Martian atmosphere. Flow will be in the range of Re \u3c 20,000, creating extreme conditions not typically examined. A Blade Element Momentum Theory (BEMT) algorithm is developed using a variety of corrections designed specifically for low Reynolds number and rotational flows. Due to both the simplicity of the basic BEMT formulation, corrections are easy to put in place and often necessary to achieve accurate estimates. Aerodynamic coefficients are determined from XFOIL code, and have questionable accuracy in this regime. To account for this, a correction model is developed by comparing XFOIL results to experimental results of airfoils at low Re. This is all tested against a previous low Re propeller experiment. The results of this comparison are used to adjust the values in the correction, to produce more accurate results for theoretical design. From here, a design philosophy for the propeller is developed using established methods and previous experimental data. High thrust is prioritized, with efficiency being a secondary concern. A hard mach limit of 0.7 is set to avoid major drag penalties, limiting the usable ranges of RPM and radius. Airfoil designs are then examined, based on previous designs, theoretical intuition, and experimental data. A modified version of the S1223 airfoil is adopted for its favorably high Clmax and high stall angle. From here, optimization can be used to determine the final dimensions of the propeller. The BEMT algorithm is used to create a broad set of data, over a range of design variables, which is then fitted to thrust and efficiency functions using non-linear regression. A Non-Dominated Sorting Genetic Algorithm (NSGA) is well suited to optimizing multiple objective functions with multiple design variables, and thus is adopted to optimize the design. The results of the optimization confirm previously published theories, and produce three possible propeller designs, a high thrust model, a high efficiency model, and a compromise between the two. These designs were then modeled, meshed and simulated using the ANSYS Fluent software suite. BEMT thrust estimates were found to be within an average absolute error of ~41% from the simulated results, while moment was within an average absolute error of ~104%. This discrepancy can likely be attributed to the inaccurate drag data being sent into the BEMT algorithm, and the lack of a method to correct said data. With a procedure established for design and testing, new propellers can be created and verified, likely with improvements in accuracy from the initial estimates

Most Reported Genetic Associations with General Intelligence Are Probably False Positives

General intelligence (g) and virtually all other behavioral traits are heritable. Associations between g and specific single-nucleotide polymorphisms (SNPs) in several candidate genes involved in brain function have been reported. We sought to replicate published associations between g and 12 specific genetic variants (in the genes DTNBP1, CTSD, DRD2, ANKK1, CHRM2, SSADH, COMT, BDNF, CHRNA4, DISC1, APOE, and SNAP25) using data sets from three independent, well-characterized longitudinal studies with samples of 5,571, 1,759, and 2,441 individuals. Of 32 independent tests across all three data sets, only 1 was nominally significant. By contrast, power analyses showed that we should have expected 10 to 15 significant associations, given reasonable assumptions for genotype effect sizes. For positive controls, we confirmed accepted genetic associations for Alzheimer’s disease and body mass index, and we used SNP-based calculations of genetic relatedness to replicate previous estimates that about half of the variance in g is accounted for by common genetic variation among individuals. We conclude that the molecular genetics of psychology and social science requires approaches that go beyond the examination of candidate genes.Economic

The Promises and Pitfalls of Genoeconomics

This article reviews existing research at the intersection of genetics and economics, presents some new findings that illustrate the state of genoeconomics research, and surveys the prospects of this emerging field. Twin studies suggest that economic outcomes and preferences, once corrected for measurement error, appear to be about as heritable as many medical conditions and personality traits. Consistent with this pattern, we present new evidence on the heritability of permanent income and wealth. Turning to genetic association studies, we survey the main ways that the direct measurement of genetic variation across individuals is likely to contribute to economics, and we outline the challenges that have slowed progress in making these contributions. The most urgent problem facing researchers in this field is that most existing efforts to find associations between genetic variation and economic behavior are based on samples that are too small to ensure adequate statistical power. This has led to many false positives in the literature. We suggest a number of possible strategies to improve and remedy this problem: (a) pooling data sets, (b) using statistical techniques that exploit the greater information content of many genes jointly, and (c) focusing on economically relevant traits that are most proximate to known biological mechanisms.EconomicsSociolog

Natural Expectations, Macroeconomic Dynamics, and Asset Pricing

How does an economy behave if (1) fundamentals are truly hump-shaped, exhibiting momentum in the short run and partial mean reversion in the long run, and (2) agents do not know that fundamentals are hump-shaped and base their beliefs on parsimonious models that they fit to the available data? A class of parsimonious models leads to qualitatively similar biases and generates empirically observed patterns in asset prices and macroeconomic dynamics. First, parsimonious models will robustly pick up the short-term momentum in fundamentals but will generally fail to fully capture the long-run mean reversion. Beliefs will therefore be characterized by endogenous extrapolation bias and pro-cyclical excess optimism. Second, asset prices will be highly volatile and exhibit partial mean reversion—i.e., overreaction. Excess returns will be negatively predicted by lagged excess returns, P/E ratios, and consumption growth. Third, real economic activity will have amplified cycles. For example, consumption growth will be negatively auto-correlated in the medium run. Fourth, the equity premium will be large. Agents will perceive that equities are very risky when in fact long-run equity returns will co-vary only weakly with long-run consumption growth. If agents had rational expectations, the equity premium would be close to zero. Fifth, sophisticated agents—i.e., those who are assumed to know the true model—will hold far more equity than investors who use parsimonious models. Moreover, sophisticated agents will follow a counter-cyclical asset allocation policy. These predicted effects are qualitatively confirmed in U.S. data.

Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma

Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management

Propuesta de mejora en la gestión de abastecimiento de materiales de embalaje del servicio de carga para la reducción de costos logísticos en una empresa del sector aeroportuario

El presente trabajo tiene como objetivo principal proponer una mejora en la gestión de abastecimiento para reducir los costos logísticos en una empresa del Sector Aeroportuario. Para esto se identificaron los problemas que afectaban al crecimiento de la organización y con ayuda de herramientas como la matriz de inventario y encuestas realizadas tanto al personal operativo como administrativo, se pudo obtener la suficiente información para detectar los problemas más relevantes. Se identificaron las variables tanto dependiente como independientes con sus respectivos indicadores y bajo un previo análisis de la situación actual se detectó que no contaban con un método de abastecimiento adecuado, por lo que se propuso una mejora en el mismo por medio del modelo EOQ, el cual luego de su implementación logró equilibrar las cantidades de pedido con respecto al consumo y permitió realizar una estandarización en el proceso de compras, reduciendo así los tiempos por generación de pedido de 39 min en el escenario actual a 28 min en el escenario propuesto bajo la implementación del modelo EOQ, de la mano a esta reducción de tiempos se suma el ahorro generado por los costos por generación de pedido, ya que estos representan un 28%. Por otro lado, también se logró incrementar la rotación de inventarios un 94% y a su vez se redujeron los días de inventario un 47%, esto a razón que el modelo del lote económico de pedido permitió ser más preciso en el abastecimiento de los materiales de embalaje del servicio de carga. Junto a esta mejora se logró reducir los costos de almacenamiento un 48%, puesto que el modelo de abastecimiento EOQ es bastante preciso en base a los consumos y no deja tener mucho inventario.The main objective of this work is to propose an improvement in supply management to reduce logistics costs in a company in the Airport Sector. For this, the problems that affect the growth of the organization were identified and with the help of tools such as the inventory matrix and surveys carried out both to operational and administrative personnel, enough information could be obtained to detect the most relevant problems. Both the dependent and independent variables were identified with their indicators and, under a previous analysis of the current situation, it was detected that they did not have an adequate supply method, for which an improvement was proposed through the EOQ model, which After its implementation, it managed to balance the order quantities with respect to consumption and carry out a standardization in the purchasing process, thus reducing the times per order generation from 39 min in the current scenario to 28 min in the scenario proposed under the implementation of the EOQ model, hand in hand with this reduction in time is added the savings generated by the costs per order generation, since these represent 28%. On the other hand, it was also possible to increase inventory turnover by 94% and, in turn, inventory days were reduced by 47%, this because the EOQ model will be more precise in supplying the packaging materials of the service loading. Together with this improvement, it was possible to reduce storage costs by 48%, since the EOQ supply model is quite accurate based on consumption and does not allow to have much inventory

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics