500 resultados para Portfolios


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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.

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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 Eurozone, and credit-supply shocks which arise from reductions in borrowing abilities during bank distress. We document het- erogeneous responses to these two types of shocks. While households with large holdings of secu- rities from stressed Eurozone countries (Greece, Ireland, Italy, Portugal, and Spain) decrease the degree of concentration in their security portfolio as a result of the Eurozone crisis, non-financial firms with similar levels of holdings from stressed Eurozone countries do not. Credit-supply shocks at the bank level (caused by bank distress) result in lower concentration, for both households and non-financial corporations. We also show that only shocks to corporate credit bear ramifications on bank clients’ portfolio concentration, while shocks in retail credit are inconsequential. Our results are robust to falsification tests, propensity score matching techniques, and instrumental variables estimation.

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A kockázat jó mérése és elosztása elengedhetetlen a bankok, biztosítók, befektetési alapok és egyéb pénzügyi vállalkozások belső tőkeallokációjához vagy teljesítményértékeléséhez. A cikkben bemutatjuk, hogy a koherens kockázati mértékek axiómáit nem likvid portfóliók esetén is el lehet várni. Így mérve a kockázatot, ismertetünk a kockázatelosztásra vonatkozó két kooperatív játékelméleti cikket. Az első optimista, eszerint mindig létezik stabil, az alegységek minden koalíciója által elfogadható, általános módszer a kockázat (tőke) elosztására. A második cikk pesszimista, mert azt mondja ki, hogy ha a stabilitás mellett igazságosak is szeretnénk lenni, akkor egy lehetetlenségi tételbe ütközünk. / === / Measuring and allocating risk properly are crucial for performance evaluation and internal capital allocation of portfolios held by banks, insurance companies, investment funds and other entities subject to fi nancial risk. We argue that the axioms of coherent measures of risk are valid for illiquid portfolios as well. Then, we present the results of two papers on allocating risk measured by a coherent measure of risk. Assume a bank has some divisions. According to the fi rst paper there is always a stable allocation of risk capital, which is not blocked by any coalition of the divisions, that is there is a core compatible allocation rule (we present some examples for risk allocation rules). The second paper considers two more natural requirements, Equal Treatment Property and Strong Monotonicity. Equal Treatment Property makes sure that similar divisions are treated symmetrically, that is if two divisions make the same marginal risk contribution to all the coalition of divisions not containing them, then the rule should allocate them the very same risk capital. Strong Monotonicity requires that if the risk environment changes in such a way that the marginal contribution of a division is not decreasing, then its allocated risk capital should not decrease either. However, if risk is evaluated by any coherent measure of risk, then there is no risk allocation rule satisfying Core Compatibility, Equal Treatment Property and Strong Monotonicity, we encounter an impossibility result.