954 resultados para mean-variance estimation


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Aquesta tesi té la intenció de realitzar una contribució metodològica en el camp de la direcció estratègica, per mitjà de tres objectius: la revisió del concepte de risc ex post o realitzat per l'àmbit de la direcció estratègica; la concreció d'aquest concepte en una mesura de risc vàlida; i l'exploració de les possibilitats i l'interès de la descomposició del risc en diferents determinants que puguin explicar-ne la seva naturalesa. El primer objectiu es du a terme prenent com a base el concepte intuïtiu de risc i revisant la literatura en els camps més afins, especialment en la teoria comportamental de la decisió i la direcció estratègica. L'anàlisi porta a formular el risc ex post d'una activitat com el grau en què no s'han assolit els objectius per a aquesta activitat. La concreció d'aquesta definició al camp de la direcció estratègica implica que els objectius han de portar a l'obtenció de l'avantatge competitiu sostenible, el que descobreix l'interès de realitzar la mesura del risc a curt termini, és a dir, estàticament, i a llarg termini, és a dir, dinàmicament, pel que es defineix una mesura de Risc Estàtic i una altra de Risc dinàmic, respectivament. En l'anàlisi apareixen quatre dimensions conceptuals bàsiques a incorporar en les mesures: sign dependence, relativa, longitudinal i path dependence. Addicionalment, la consideració de que els resultats puguin ser cardinals o ordinals justifica que es formulin les dues mesures anteriors per a resultats cardinals i, en segon lloc, per a resultats ordinals. Les mesures de risc que es proposen sintetitzen els resultats ex post obtinguts en una mesura de centralitat relativa dels resultats, el Risc Estàtic, i una mesura de la tendència temporal dels resultats, el Risc Dinàmic. Aquesta proposta contrasta amb el plantejament tradicional dels models esperança-variància. Les mesures desenvolupades s'avaluen amb un sistema de propietats conceptuals i tècniques que s'elaboren expressament en la tesi i que permeten demostrar el seu gra de validesa i el de les mesures existents en la literatura, destacant els problemes de validesa d'aquestes darreres. També es proporciona un exemple teòric il·lustratiu de les mesures proposades que dóna suport a l'avaluació realitzada amb el sistema de propietats. Una contribució destacada d'aquesta tesi és la demostració de que les mesures de risc proposades permeten la descomposició additiva del risc si els resultats o diferencials de resultats es descomponen additivament. Finalment, la tesi inclou una aplicació de les mesures de Risc Estàtic i Dinàmic cardinals, així com de la seva descomposició, a l'anàlisi de la rendibilitat del sector bancari espanyol, en el període 1987-1999. L'aplicació il·lustra la capacitat de les mesures proposades per a analitzar la manifestació de l'avantatge competitiu, la seva evolució i naturalesa econòmica. En les conclusions es formulen possibles línees d'investigació futures.

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Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

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The “case for property” in the mixed-asset portfolio is a topic of continuing interest to practitioners and academics. Such an analysis typically is performed over a fixed period of time and the optimum allocation to property inferred from the weight assigned to property through the use of mean-variance analysis. It is well known, however, that the parameters used in the portfolio analysis problem are unstable through time. Thus, the weight proposed for property in one period is unlikely to be that found in another. Consequently, in order to assess the case for property more thoroughly, the impact of property in the mixed-asset portfolio is evaluated on a rolling basis over a long period of time. In this way we test whether the inclusion of property significantly improves the performance of an existing equity/bond portfolio all of the time. The main findings are that the inclusion of direct property into an existing equity/bond portfolio leads to increase or decreases in return, depending on the relative performance of property compared with the other asset classes. However, including property in the mixed-asset portfolio always leads to reductions in portfolio risk. Consequently, adding property into an equity/bond portfolio can lead to significant increases in risk-adjusted performance. Thus, if the decision to include direct property in the mixed-asset portfolio is based upon its diversification benefits the answer is yes, there is a “case for property” all the time!

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Modern Portfolio Theory (MPT) has been advocated as a more rational approach to the construction of real estate portfolios. The application of MPT can now be achieved with relative ease using the powerful facilities of modern spreadsheet, and does not necessarily need specialist software. This capability is to be found in the use of an add-in Tool now found in several spreadsheets, called an Optimiser or Solver. The value in using this kind of more sophisticated analysis feature of spreadsheets is increasingly difficult to ignore. This paper examines the use of the spreadsheet Optimiser in handling asset allocation problems. Using the Markowitz Mean-Variance approach, the paper introduces the necessary calculations, and shows, by means of an elementary example implemented in Microsoft's Excel, how the Optimiser may be used. Emphasis is placed on understanding the inputs and outputs from the portfolio optimisation process, and the danger of treating the Optimiser as a Black Box is discussed.

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In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.