Jeu d'argent

thumb|Le Caravage, Les Tricheurs, 1594-1595. Le jeu d'argent est la pratique d'un jeu associée à un intéressement financier à l'issue de la partie. Chaque joueur engage un certain montant financier dans le jeu, qui sera tout ou partie perdu, ou qui sera augmenté en cas de gain. Ces jeux sont pour la plupart des jeux de hasard pur, ou de hasard raisonné. La prudence est de mise pour éviter la ruine du joueur. Les probabilités de gains des différents types de jeu sont variables et une bonne gestion des mises et de ses cartes peuvent permettre de réaliser quelques gains. Cependant, il faut bien garder à l'idée que les chances de gagner sont rarement égales aux chances de perdre. Un joueur sera forcément perdant au long terme au vu des probabilités variables selon les jeux (et les établissements pour les machines à sous par exemple). Types de jeux d'argent On trouve différents types de jeux dans cette catégorie :

le poker : jeu de carte et de hasard raisonné
le black

Investigating signal integration with canonical correlation analysis of fMRI brain activation data

Kerstin Preuschoff

How the brain integrates signals from specific areas has been a longstanding critical question for neurobiologists. Two recent observations suggest a new approach to fMRI data analysis of this question. First, in many instances, the brain analyzes inputs by decomposing the information along several salient dimensions. For example, earlier work demonstrated that the brain splits a monetary gamble in terms of expected reward (ER) and variance of the reward (risk) [Preuschoff, K., Bossaerts, P., Quartz, S., 2006. Neural differentiation of expected reward and risk in human subcortical structures. Neuron 51, 381-390]. However, since ER and risk activate separate brain regions, the brain needs to integrate these activations to obtain an overall evaluation of the gamble. Second, recent evidence suggests that the correlation of the activity between neurons may serve a specific organizational purpose [Romo, R., Hernandez, A., Zainos, A., Salinas, E., 2003. Correlated neuronal discharges that increase coding efficiency during perceptual discrimination. Neuron 38, 649-657; Salinas, E., Sejnowski, T.J., 2001. Correlated neuronal activity and the flow of neural information. Nat. Rev. Neurosci. 2, 539]. Specifically, it is hypothesized that correlations allow brain regions to integrate several signals in a way that minimizes noise. Under this hypothesis, we show here that canonical correlation analysis of fMRI data identifies how the signals from several regions are combined. A general linear model then verifies whether the identified combination indeed activates a projection area in the brain. We illustrate the proposed procedure on data recorded while human subjects played a simple card game. We show that the brain adds the signals of ER and risk to form a measure that activates the medial prefrontal cortex, consistent with the role of this brain structure in the evaluation of monetary gambles. (c) 2008 Elsevier Inc. All rights reserved.

2008

Non-myopic betas

Semyon Malamud

An overlapping generations model with investors having heterogeneous investment horizons leads to a two-factor asset pricing model. The risk premiums are determined by the exposure to the market (myopic betas) and the future return on the efficient portfolio (non-myopic betas), which is identified nonparametrically from equilibrium. Non-myopic betas are priced in the cross-section of stocks, producing increasing and economically significant risk-return relation. In the model with funding constraints, low non-myopic beta stocks deliver higher risk-adjusted returns. Empirically, a betting against non-myopic beta portfolio generates superior performance relative to common factor models and is negatively correlated with the market betting against beta portfolio.

2018

Investigating signal integration with canonical correlation analysis of fMRI brain activation data

Kerstin Preuschoff

2008

Investigating signal integration with canonical correlation analysis of fMRI brain activation data

Non-myopic betas

Categorization of Monetary Gambles in the Human Brain

Investigating signal integration with canonical correlation analysis of fMRI brain activation data

Categorization of Monetary Gambles in the Human Brain

Non-myopic betas