Hindsight bias, risk perception and investment performance

Once they have observed information, hindsight biased agents fail to remember how ignorant they were initially, “they knew it all along.” We formulate a theoretical model of this bias, providing a foundation for empirical measures, and implying that hindsight biased agents learning about volatility will underestimate it. In an experiment involving 67 students from Mannheim University, we find that hindsight bias reduces volatility estimates. In another experiment, involving 85 investment bankers in London and Frankfurt, we find that more biased agents have lower performance. These findings are robust to differences in location, information, overconfidence and experience

A FACED lift for cerebral blood flow imaging

ISSN:0027-8424ISSN:1091-649

Quantitative modeling of laser speckle imaging

We have analyzed the image formation and dynamic properties in laser speckle imaging (LSI) both experimentally and with Monte-Carlo simulation. We show for the case of a liquid inclusion that the spatial resolution and the signal itself are both significantly affected by scattering from the turbid environment. Multiple scattering leads to blurring of the dynamic inhomogeneity as detected by LSI. The presence of a non-fluctuating component of scattered light results in the significant increase in the measured image contrast and complicates the estimation of the relaxation time. We present a refined processing scheme that allows a correct estimation of the relaxation time from LSI data.Comment: submitted to Optics Letter

Simulation des relations populations - ressources naturelles : prototype de modèle pour un terroir du Nord Cameroun

International audienceNous présentons ici un modèle qui permet de comparer l'impact de la croissance démographique sur la gestion des ressources naturelles dans un système agraire des zones de savane africaine. Le modèle montre comment une population en croissance consomme de plus en plus de ressources jusqu'à un certain seuil en dessous duquel la productivité de ces ressources est affectée. Le modèle réagit alors en investissant dans des techniques de régénération des ressources. L'objectif principal est de comparer plusieurs techniques de restauration de la fertilité comme l'intégration agriculture élevage, l'agroforesterie ou le semis sous couverture végétale. Pour l'instant le modèle est à l'état de prototype. Le système agraire en question est imaginaire mais nous avons appliqué des chiffres provenant de la littérature technique sur les cycles de matière organique ou de biomasse dans les zones de savane. Les résultats du modèle décrivent une courbe en U avec une phase de dégradation du stock initial et une phase de régénération. Le modèle suggère que le potentiel existe pour maintenir une agriculture durable en combinant plusieurs techniques de restauration. Toutefois il suggère aussi qu'il faille des économies d'échelle pour que la productivité du travail ne décline pas. En absence d'économie d'échelle il est probable qu'une fois les seuils de dégradation des ressources atteints, les populations migrent vers des zones moins peuplées. (Résumé d'auteur

Overreaction and investment choices : an experimental analysis

We study the degree of overreaction and the relation of overreaction and psychological biases as well as financial consequences of overreaction in a controlled experimental setting with 104 participants. The majority of participants tend to overreact, however, the degree of overreaction is heterogeneous. A few subjects even underreact. We also measure the overconfidence of the participants with a miscalibration scale. In line with theoretical predictions we find that more overconfident subjects overreact more. We also find that overreaction is associated with higher levels of risk taking after good signals and lower levels of risk taking after bad signals. Finally, overreaction harms portfolio efficiency, as measured by the Sharpe ratio

Laser Speckle Imaging of Cerebral Blood Flow

Optical imaging of cerebral hemodynamics has been used extensively to investigate the complex interplay between neurons and the blood-borne supply of oxygen and energy substrates. Among several techniques, the so-called laser speckle imaging (LSI) has found widespread applications for studying (patho-)physiological aspects of neurovascular coupling. LSI is a rather simple and cost-effective method to acquire two-dimensional maps of cerebral blood flow from the cortex of experimental animals. In this chapter, we introduce the physical underpinnings as well as the most important technical and practical aspects of its implementation

Segmentation and detection of cattle branding images using CNN and SVM classification

This article presents a hybrid method that uses Convolutional Neural Networks (CNN) to segmentation and Support Vector Machines (SVM) to detection the brandings. The experiments were performed using a cattle branding images. Metrics of Overall Accuracy, Recall, Precision, Kappa Coefficient, and Processing Time were used in order to assess the proposed tool. The results obtained here were satisfactory, reaching a Overall Accuracy of 93% in the first experiment with 39 brandings and 1,950 sample images, and 95% of accuracy in the second experiment, with the same 39 brandings, but with 2,730 sample images. The processing time attained in the experiments was 32s and 42s, respectively