Not all family firms are equal: The moderating effect of family involvement on the political risk exposure of the foreign direct investment portfolio. Preliminary evidence from Spanish multinational enterprises

We investigate the effect of political risk (PR) exposure and family control on the internationalization strategy of multinational enterprises (MNEs) using social capital theory. Our results from a negative binomial cross‐sectional analysis in 2007 of Spanish MNEs show family ownership or the limited presence of family members on the board has no effect on internationalization. However, when the conceptualization of family firms (FFs) includes majority ownership and board presence, we find a direct negative effect on their internationalization scope but a positive moderating effect on the relationship between the exposure to PR and internationalization scope. FFs have some specific advantages suitable to be employed in their corporate political activity allowing them to develop long‐lasting relationships with relevant political actors. By disentangling the effects of family control on internationalization and PR, this article explains how FFs can be simultaneously risk‐willing and risk‐averse.     

Ruin Probabilities And Capital Requirement for Open Automobile Portfolios With a Bonus-Malus System Based on Claim Counts

For a large motor insurance portfolio, on an open environment, we study the impact of experience rating in finite and continuous time ruin probabilities. We consider a model for calculating ruin probabilities applicable to large portfolios with a Markovian Bonus-Malus System (BMS), based on claim counts, for an automobile portfolio using the classical risk framework model. New challenges are brought when an open portfolio scenario is introduced. When compared with a classical BMS approach ruin probabilities may change significantly. By using a BMS of a Portuguese insurer, we illustrate and discuss the impact of the proposed formulation on the initial surplus required to target a given ruin probability. Under an open portfolio setup, we show that we may have a significant impact on capital requirements when compared with the classical BMS, by having a significant reduction on the initial surplus needed to maintain a fixed level of the ruin probability.     

The optimal method for pricing Bermudan options by simulation

Least‐squares methods enable us to price Bermudan‐style options by Monte Carlo simulation. They are based on estimating the option continuation value by least‐squares. We show that the Bermudan price is maximized when this continuation value is estimated near the exercise boundary, which is equivalent to implicitly estimating the optimal exercise boundary by using the value‐matching condition. Localization is the key difference with respect to global regression methods, but is fundamental for optimal exercise decisions and requires estimation of the continuation value by iterating local least‐squares (because we estimate and localize the exercise boundary at the same time). In the numerical example, in agreement with this optimality, the new prices or lower bounds (i) improve upon the prices reported by other methods and (ii) are very close to the associated dual upper bounds. We also study the method's convergence.     

When can you immunize a bond portfolio?

This paper presents a condition equivalent to the existence of a Riskless Shadow Asset that guarantees a minimum return when the asset prices are convex functions of interest rates or other state variables. We apply this lemma to immunize default-free and option-free coupon bonds and reach three main conclusions. First, we give a solution to an old puzzle: why do simple duration matching portfolios work well in empirical studies of immunization even though they are derived in a model inconsistent with equilibrium and shifts on the term structure of interest rates are not parallel, as assumed? Second, we establish a clear distinction between the concepts of immunized and maxmin portfolios. Third, we develop a framework that includes the main results of this literature as special cases. Next, we present a new strategy of immunization that consists in matching duration and minimizing a new linear dispersion measure of immunization risk.     

Stockbot: a monitoring and acting software agent for stock markets

Stockbot is a software agent designed for the task of monitoring an electronic stock market in order to execute investor purchase or sale orders. Stockbot represents a tool for managing the dynamical complexity of electronic stock markets by establishing a virtual portfolio manager. Its main goal is to exhibit a behaviour which is a timely, continuous, dynamical response to changes in the market situations in accordance to the user profile and goals. The software agent maintains and dynamically updates a user model which records histories of previous user orders, patterns of user observed behaviour, and user preferences and goals. The software architecture integrates conventional and knowledge-based software technologies such as conditional and iterative planning, continuous conditions monitoring, robust failure management, inter-agent communication primitives and events networks. A Dynamical Query Language is used to describe stockbot behaviour. Copyright © 1999 John Wiley & Sons, Ltd.     

Firm and industry effects within strategic management: an empirical examination

This study brings out the complementarities between resource-based and industrial organization schools within strategic management through an empirical examination of firm and industry effects. A variance component analysis of 264 single-business companies from 69 industries using 5- and 15-year periods suggests that firm effects are more important than industry effects on firm performance, but not on core strategies such as technology and marketing. The findings also point to the need to study core strategies at lower levels of aggregation to understand the sources of competitive advantage. © 1998 John Wiley & Sons, Ltd.     

A comparison of qualitatively and quantitatively driven analytic procedures of psychotherapeutic group sessions with deviant adolescents

The present paper deals with the therapy-related change in a group of deviant adolescents attending a therapeutic facility. The main issue of two studies reported here is to identify pattern of changes through different methods. The paper describes how the mixing of two different types of analysis may yield a more complex and complete view of the data. The analyses were performed at the same time: the first part (study 1), which was of a clinical–quantitative nature, involved picking out changerelated features through the analysis of the frequency of lemmas in the content of the sessions; the second part (study 2) had a qualitative orientation and traced the pattern of narrative themes in the sessions during the course of time. In both studies, the same data were analyzed at the same times, though each study adopted a different approach. While both approaches focused on change, the results brought out different aspects: the study that adopted the quantitative/clinical approach highlighted changerelated problems and proposed an explanation in terms of the “deviant peer effect”; by contrast, the qualitative study underlined the possibilities offered by change and viewed therapeutic change in terms of the shift in narrative themes from the detachment and lack of responsibility initially shown by the youths towards progressive maturation that may have been due to the efficacy of the therapy. The discussion of results brings us to consider the fuzzy set approach for future research into the field of criminology and group therapy. In conclusion, the paper shows that looking at the same data through two different methodological “lenses” yields different, and only apparently contradictory, conclusions.