Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

New Product Portfolio Performance in Family Firms

This study investigates the relationship between top management team (TMT) innovation orientation and new product portfolio performance in small and medium-sized family firms by exploring two family firm-specific sources of TMT diversity as moderators: the number of generations involved in the TMT and the ratio of family members in the TMT. Results indicate that family-induced diversity in the TMT has opposing moderating effects. Although a positive relationship exists between TMT innovation orientation and new product portfolio performance when multiple generations are involved in the TMT, TMT innovation orientation and new product portfolio performance experience a negative relationship when the ratio of family members in the TMT is high. The study discusses theoretical and managerial implications of the findings and develops avenues for future research.

Lernprozesse dokumentieren, reflektieren und beurteilen. Lerntagebuch und Portfolio in Bildungsforschung und Bildungspraxis

Die Beiträge greifen "den Wandel von einer Lehr- hin zu einer Lernkultur" auf und konzentrieren sich dabei auf "zwei Indikatoren dieses Wandels: die Einführung von Lerntagebüchern und die Implementierung von Portfolios im Bildungsbereich, und zwar im schulischen Unterricht, in der Lehrer-Grundausbildung sowie in der Weiterbildung. Der Lerntagebuch- und Portfolio-Ansatz implizieren eine bestimmte Haltung gegenüber dem Lernen und Lehren. Der Einsatz von Tagebüchern und Portfolios führt Lehrende dazu, ihren Unterricht für neue Zugänge zu öffnen und ihre Rolle als Lernbegleiter/innen und -berater/innen zu professionalisieren. Andererseits erfordern Tagebücher und Portfolios von Lernenden eine aktive, selbstreflexive und eigenverantwortliche Auseinandersetzung mit ihrem Lernprozess. In diesem Band werden zum einen praxisbezogene Erfahrungen, zum anderen aktuelle Erkenntnisse aus der Forschung zum Potenzial des Lerntagebuch- und Portfolio-Ansatzes präsentiert. Jeweils drei bis fünf Beiträge zum Kontext Schule, Hochschule und Weiterbildung sind drei Hauptteilen zugeordnet: 1. Grundüberlegungen zur neuen Lernkultur und zur Arbeit mit Lerntagebuch bzw. Portfolio; 2. Lerntagebücher in Forschung und Praxis; 3. Portfolios in Forschung und Praxis.

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.