29 resultados para Portfolios

em Aston University Research Archive


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Lifelong learning is a ‘keystone’ of educational policies (Faure, 1972) where the emphasis on learning shifts from teacher to learner. Higher Education (HE) institutions should be committed to developing lifelong learning, that is promoting learning that is flexible, diverse and relevant at different times, and in different places, and is pursued throughout life. Therefore the HE sector needs to develop effective strategies to encourage engagement in meaningful learning for diverse student populations. The use of e-portfolios, as a ‘purposeful aggregation of digital items’ (Sutherland & Powell, 2007), can meet the needs of the student community by encouraging reflection, the recording of experiences and achievements, and personal development planning (PDP). The use of e-portfolios also promotes inclusivity in learning as it provides students with the opportunity to articulate their aspirations and take the first steps along the pathway of lifelong learning. However, ensuring the uptake of opportunities within their learning is more complex than the students simply having access to the software. Therefore it is argued here that crucial to the effective uptake and engagement of the e-portfolio is embedding it purposefully within the curriculum. In order to investigate effective implementation of e-portfolios an explanatory case study on their use was carried out, initially focusing on 3 groups of students engaged in work-based learning and professional practice. The 3 groups had e-Portfolios embedded and assessed at different levels. Group 1 did not have the e-Portfolio embedded into their curriculum nor was the e-Portfolio assessed. Group 2 had the e-Portfolio embedded into the curriculum and formatively assessed. Group 3 also had the e-Portfolio embedded into the curriculum and were summatively assessed. Results suggest that the use of e-Portfolios needs to be integral to curriculum design in modules rather than used as an additional tool. In addition to this more user engagement was found in group 2 where the e-Portfolio was formatively assessed only. The implications of this case study are further discussed in terms of curriculum development.

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This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA.

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The stock market response to corporate scandals and the use of the internet by pressure groups have sensitized boards to the risk of reputation loss. Particularly at risk are companies using corporate brands whose fame and spread makes them particularly vulnerable. This study looks at these and other pressures on branding and investigates if and how leading companies have responded in the deployment of their brand portfolios. A repeat audit of the use of brand portfolios by leading companies using exactly the same method used over a decade ago reveals much change. Brand structures of the 20 companies investigated have indeed changed but not uniformly in extent or direction.

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This study examines the changes in brand structures based on a repeat audit of brand portfolios by leading grocery product suppliers. It compares results from content analyses of four hundred leading suppliers' brands sold to Tesco and Sainsbury's in 1994 and 2004. The brand structures used have changed although not uniformly in extent or direction. There is now more complexity in the way brand names are used. An extended typology of brand structures is incorporated. Propositions drawn from latest thinking on the use of brand portfolios are compared with the findings implications discussed.

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The techniques and insights from two distinct areas of financial economic modelling are combined to provide evidence of the influence of firm size on the volatility of stock portfolio returns. Portfolio returns are characterized by positive serial correlation induced by the varying levels of non-synchronous trading among the component stocks. This serial correlation is greatest for portfolios of small firms. The conditional volatility of stock returns has been shown to be well represented by the GARCH family of statistical processes. Using a GARCH model of the variance of capitalization-based portfolio returns, conditioned on the autocorrelation structure in the conditional mean, striking differences related to firm size are uncovered.

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This paper will show that short horizon stock returns for UK portfolios are more predictable than suggested by sample autocorrelation co-efficients. Four capitalisation based portfolios are constructed for the period 1976–1991. It is shown that the first order autocorrelation coefficient of monthly returns can explain no more than 10% of the variation in monthly portfolio returns. Monthly autocorrelation coefficients assume that each weekly return of the previous month contains the same amount of information. However, this will not be the case if short horizon returns contain predictable components which dissipate rapidly. In this case, the return of the most recent week would say a lot more about the future monthly portfolio return than other weeks. This suggests that when predicting future monthly portfolio returns more weight should be given to the most recent weeks of the previous month, because, the most recent weekly returns provide the most information about the subsequent months' performance. We construct a model which exploits the mean reverting characteristics of monthly portfolio returns. Using this model we forecast future monthly portfolio returns. When compared to forecasts that utilise the autocorrelation statistic the model which exploits the mean reverting characteristics of monthlyportfolio returns can forecast future returns better than the autocorrelation statistic, both in and out of sample.

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This paper demonstrates how the autocorrelation structure of UK portfolio returns is linked to dynamic interrelationships among the component securities of that portfolio. Moreover, portfolio return autocorrelation is shown to be an increasing function of the number of securities in the portfolio. Since the security interrelationships seemed to be more a product of their history of non-synchronous trading than of systematic industry-related phenomena, it should not be possible to exploit the high levels of return persistence using trading rules. We show that rules designed to exploit this portfolio autocorrelation structure do not produce economic profits.

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Developing a strategy for online channels requires knowledge of the effects of customers' online use on their revenue and cost to serve, which ultimately influence customer profitability. The authors theoretically discuss and empirically examine these effects. An empirical study of retail banking customers reveals that online use improves customer profitability by increasing customer revenue and decreasing cost to serve. Moreover, the revenue effects of online use are substantially larger than the cost-to-serve effects, although the effects of online use on customer revenue and cost to serve vary by product portfolio. Self-selection effects also emerge and can be even greater than online use effects. Ignoring self-selection effects thus can lead to poor managerial decision-making.

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This paper explains how dynamic client portfolios can be a source of ambidexterity (i.e., exploration and exploitation) for knowledge-intensive firms (KIFs). Drawing from a unique qualitative dataset of firms in the global reinsurance market, we show how different types of client relationships underpin a dynamic client portfolio and become a source of ambidexterity for a KIF. We develop a process model to show how KIFs attain knowledge by segmenting their client portfolios, use that knowledge to explore and exploit within and across their client relationships, and dynamically adjust their client portfolios over time. Our study contributes to the literature on external sources of ambidexterity and dynamic management of client knowledge within KIFs.

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This article examines whether UK portfolio returns are time varying so that expected returns follow an AR(1) process as proposed by Conrad and Kaul for the USA. It explores this hypothesis for four portfolios that have been formed on the basis of market capitalization. The portfolio returns are modelled using a kalman filter signal extraction model in which the unobservable expected return is the state variable and is allowed to evolve as a stationary first order autoregressive process. It finds that this model is a good representation of returns and can account for most of the autocorrelation present in observed portfolio returns. This study concludes that UK portfolio returns are time varying and the nature of the time variation appears to introduce a substantial amount of autocorrelation to portfolio returns. Like Conrad and Kaul if finds a link between the extent to which portfolio returns are time varying and the size of firms within a portfolio but not the monotonic one found for the USA. © 2004 Taylor and Francis Ltd.

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We use a unique dataset with bank clients’ security holdings for all German banks to examine how macroeconomic shocks affect asset allocation preferences of households and non-financial firms. Our analysis focuses on two alternative mechanisms which can influence portfolio choice: wealth shocks, which are represented by the sovereign debt crisis in the Euro area, and credit-supply shocks which arise from reductions in borrowing abilities during bank distress. While households with large holdings of securities from stressed Euro area countries (Greece, Ireland, Italy, Portugal, and Spain) de-crease the degree of concentration in their security portfolio as a result of the Euro area crisis, non-financial firms with similar levels of holdings from stressed Euro area countries do not. Credit-supply shocks at the bank level result in lower concentration, for both households and non-financial corporations. Only shocks to corporate credit bear ramifications on bank clients’ portfolio concentration. Our results are robust to falsification tests, and instrumental variables estimation.