Completely Bounded Homomorphisms of the Fourier Algebras

For locally compact groups G and H let A(G) denote the Fourier algebra of G and B(H) the Fourier-Stieltjes algebra of H. Any continuous piecewise affine map alpha:Y -> G (where Y is an element of the open coset ring of H) induces a completely bounded homomorphism Phi_alpha:A(G) -> B(H) by setting Phi_alpha u(.)=u(alpha(.)) on Y and Phi_alpha u=0 off of Y. We show that if G is amenable then any completely bounded homomorphism Phi:A(G) -> B(H) is of this form; and this theorem fails if G contains a discrete nonabelian free group. Our result generalises results of P.J. Cohen, B. Host and of the first author. We also obtain a description of all the idempotents in the Fourier-Stieltjes algebras which are contractive or positive definite.Comment: 19 page

A Conceptual Model of Investor Behavior

Based on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exhibit behavioral biases. In the modeling tradition of cognitive science and intelligent systems, the investor is seen as a learning, adapting, and evolving entity that perceives the environment, processes information, acts upon it, and updates his or her internal states. This conceptual model can be used to build stylized representations of (classes of) individual investors, and further studied using the paradigm of agent-based artificial financial markets. By allowing us to implement individual investor behavior, to choose various market mechanisms, and to analyze the obtained asset prices, agent-based models can bridge the gap between the micro level of individual investor behavior and the macro level of aggregate market phenomena. It has been recognized, yet not fully explored, that these models could be used as a tool to generate or test various behavioral hypothesis.behavioral finance;financial decision making;agent-based artificial financial markets;cognitive modeling;investor behavior

The approximation property implies that convolvers are pseudo-measures

This paper (not for formal publication) grew out of the authors' attempts to understand Cowling's argument that for a locally compact group $G$ with the approximation property, we have that $PM_p(G)=CV_p(G)$ ("all convolvers are pseudo-measures".) We have ended up giving a somewhat self-contained survey of Cowling's construction of a predual for $CV_p(G)$, together with a survey of old ideas of Herz relating to Herz-Schur multipliers. Thus none of the results are new, but we make some claim to originality of presentation. We hope this account may help other researchers, and in particular, that this might spur others to study this problem

Electrophysiological evidence for different effects of working memory load on interference control in adolescents than adults

The present study investigated how the development of interference control is influenced by the development of working memory (WM) capacity during adolescence. In a dual-task, 17 adolescents (12-16years) and 19 adults (18-48years) performed a gender word-face Stroop task, while WM-capacity was manipulated by a concurrently performed N-back task. Behavior (reaction times, % errors and % misses) and event-related potentials associated with the detection (N450) of the Stroop conflict and response selection (sustained positivity; SP) were measured without or with a concurrent WM load. Adolescents had lower accuracy on N-back and Stroop trials than adults. N450 results showed Stroop conflict above temporal-occipital cortex which was suggested to be caused by processing of distracter faces. This N450 conflict response was smaller in adults and only present when holding a simultaneous WM-load, whereas adolescents' N450 conflict responses were already present without a concurrent WM-load and did not further increase with load. These N450 results indicate poorer distracter suppression in adolescence which is suggested to be due to insufficient attentional resources for top-down control. Irrespective of WM-load, adolescents also had larger parietal SP conflict responses than adults, suggesting inefficient response selection in case of activation of two conflicting responses. The main conclusion is that adolescents have worse distracter suppression than adults, caused by lower availability of resources for top-down control. (PsycINFO Database Record (c) 2011 APA, all rights reserved) (journal abstract

Modeling investor optimism with fuzzy connectives

Optimism or pessimism of investors is one of the important characteristics that determine the investment behavior in financial markets. In this paper, we propose a model of investor optimism based on a fuzzy connective. The advantage of the proposed approach is that the influence of different levels of optimism can be studied by varying a single parameter. We implement our model in an artificial financial market based on the LLS model. We find that more optimistic investors create more pronounced booms and crashes in the market, when compared to the unbiased efficient market believers of the original model. In the case of extreme optimism, the optimistic investors end up dominating the market, while in the case of extreme pessimism, the market reduces to the benchmark model of rational informed investors

A Conceptual Model of Investor Behavior

Based on a survey of behavioral finance literature, this paper presents a descriptive model of individual investor behavior in which investment decisions are seen as an iterative process of interactions between the investor and the investment environment. This investment process is influenced by a number of interdependent variables and driven by dual mental systems, the interplay of which contributes to boundedly rational behavior where investors use various heuristics and may exhibit behavioral biases. In the modeling tradition of cognitive science and intelligent systems, the investor is seen as a learning, adapting, and evolving entity that perceives the environment, processes information, acts upon it, and updates his or her internal states. This conceptual model can be used to build stylized representations of (classes of) individual investors, and further studied using the paradigm of agent-based artificial financial markets. By allowing us to implement individual investor behavior, to choose various market mechanisms, and to analyze the obtained asset prices, agent-based models can bridge the gap between the micro level of individual investor behavior and the macro level of aggregate market phenomena. It has been recognized, yet not fully explored, that these models could be used as a tool to generate or test various behavioral hypothesis