The impact of family control on firm's return

Family firm is a field of growing interest. The aim of this article is to understand whether CEOs identity impacts family firm’s stock returns. From a sample of Portuguese and Spanish family firms findings show that who manages the firms result in significantly different risk exposure. Moreover, we find that the abnormal return found by Fahlenbrach (2009) to founder-controlled firms disappear when we use valueweighted portfolios and include two new factors: market aggregate illiquidity and debt intensity to the four-factor Carhart model. Finally, our results explain why the majority of family firm is controlled by its founder.

The role of an illiquidity factor in the Portuguese stock market

This study examines the role of illiquidity (proxied by the proportion of zero returns) as an additional risk factor in asset pricing. We use Portuguese monthly data, covering the period between January 1988 and December 2008. We compute an illiquidity factor using the Fama and French [Fama, E. F., and K. R. French (1993), "Common risk factors in the returns on stocks and bonds", Journal of Financial Economics, Vol. 33, Nº. 1, pp. 3-56] procedure and analyze the performance of CAPM, Fama-French three-factor model and illiquidity-augmented versions of these models in explaining both the time-series and the cross-section of returns. Our results reveal that the effect of characteristic liquidity is subsumed by the models considered, but the risk of illiquidity is not priced in the Portuguese stock market.

A model for heterogeneous networks management and Performance evaluation

In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

Explicit series solution for a glucose-induced electrical activity model of pancreatic beta-cells

In this work, we present the explicit series solution of a specific mathematical model from the literature, the Deng bursting model, that mimics the glucose-induced electrical activity of pancreatic beta-cells (Deng, 1993). To serve to this purpose, we use a technique developed to find analytic approximate solutions for strongly nonlinear problems. This analytical algorithm involves an auxiliary parameter which provides us with an efficient way to ensure the rapid and accurate convergence to the exact solution of the bursting model. By using the homotopy solution, we investigate the dynamical effect of a biologically meaningful bifurcation parameter rho, which increases with the glucose concentration. Our analytical results are found to be in excellent agreement with the numerical ones. This work provides an illustration of how our understanding of biophysically motivated models can be directly enhanced by the application of a newly analytic method.

On the analytical solutions of the Hindmarsh-Rose neuronal model

In this article we analytically solve the Hindmarsh-Rose model (Proc R Soc Lond B221:87-102, 1984) by means of a technique developed for strongly nonlinear problems-the step homotopy analysis method. This analytical algorithm, based on a modification of the standard homotopy analysis method, allows us to obtain a one-parameter family of explicit series solutions for the studied neuronal model. The Hindmarsh-Rose system represents a paradigmatic example of models developed to qualitatively reproduce the electrical activity of cell membranes. By using the homotopy solutions, we investigate the dynamical effect of two chosen biologically meaningful bifurcation parameters: the injected current I and the parameter r, representing the ratio of time scales between spiking (fast dynamics) and resting (slow dynamics). The auxiliary parameter involved in the analytical method provides us with an elegant way to ensure convergent series solutions of the neuronal model. Our analytical results are found to be in excellent agreement with the numerical simulations.