999 resultados para Asset Structure


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This study revisits the capital structure theory and test Pecking Order Hypothesis (POH) and Static Order Trade-off theory (STOT) using Malaysian Listed firms over a period from 1999 to 2002. The evidence from pecking order model suggests that the internal fund deficiency is the most important determinant that possibly explains the issuance of new debt in Malaysian capital market despite the lower predicting power.  While static trade off-model is not fit to explain the issuance of new debt issue in Malaysian capital market. This is an interesting findings that confirm the fact that Malaysian firms do not too much care about tax-shield benefit derive from employ both debt and non-debt tax-shield. The finn's size, which is used to neutralize the size effect, appears to provide some explanation for the variation in its capital structure policy choice; however asset structure and growth no evidence of static-order-trade-off is observed in Malaysian capital market.

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Using a new dataset of 1539 Chinese small and medium-sized enterprises this article investigates the firm-level determinants of capital structure and tests them against the predictions of financial theory. Firm size and profitability are both found to be related to leverage as posited by pecking-order theory. In contrast little support is found for the predicted relationship between asset structure and leverage. These findings are discussed in relationship to their Chinese cultural context. The managerial and policy implications of the research are then explored.

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. The cotton mill industry is one of the important medium and large-scale industries in the State of Kerala. Due to the widespread development of the handloom industry in the State, there is an environment conducive to the growth of cotton spinning mills which produce yarn, the raw material required by the handloom industry. New spin— ing mills are being commissioned. But the performance of the existing cotton spinning and weaving mills in the State is not quite satisfactory. Hence an analysis has been carried out into the profitability and financial position of the industry in Kerala. The objective of the study is to make a financial analysis of the industry covering various aspects such as cost structure, productivity, asset structure, financial structure and working capital management.

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No presente estudo procuramos analisar os determinantes do crescimento das empresas familiares portuguesas, através de uma amostra de empresas familiares membros da Associação de Empresas Familiares, durante o período de 2006 a 2014. Com vista ao teste das hipóteses em estudo foram utilizados dados em painel, com modelos de efeitos fixo e aleatório. A variável dependente definida foi o crescimento das vendas. As variáveis independentes definidas foram: dimensão; idade; endividamento; endividamento de curto prazo; endividamento de médio longo prazo; produtividade da mão-de-obra; estrutura do ativo; variável dummy da crise financeira; variável dummy da administração pertencer à família; e variável dummy do género do administrador. Os resultados obtidos confirmam a dimensão, a idade e o endividamento como determinantes do crescimento; ABSTRACT: In the present study we analyzed the determinants of growth of family businesses through a sample of family businesses members of the Family Business Association, during the period between 2006 and 2014. In order to test the hypotheses under study were used panel data, with models of fixed and random effects. The Sales growth was defined as the dependent variable. The independent variables were defined: size; age; debt; short-term debt; medium and long term debt; labor productivity; asset structure; dummy variable of the financial crisis; dummy administration belong to the family; and dummy administrator gender variable. The results confirm the size, age, and debt as determinants of growth.

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Dissertação de Mestrado em Gestão Empresarial. Faculdade de Economia, Univ. do Algarve, 2004

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Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.

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Based on the consolidated statements data of the universal/commercial banks (UKbank) and non-bank financial institutions with quasi-banking licenses, this paper presents a keen necessity of obtaining data in detail on both sides (assets and liabilities) of their financial conditions and further analyses. Those would bring more adequate assessments on the Philippine financial system, especially with regard to each financial subsector's financing/lending preferences and behavior. The paper also presents a possibility that the skewed locational and operational distribution exists in the non-UKbank financial subsectors. It suggests there may be a significant deviation from the authorities' (the BSP, SEC and others) intended/anticipated financial system in the banking/non-bank financial institutions' real operations.

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Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

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The natural disasters incident that frequently hit Indonesia are floods, severe droughts, tsunamis, earth-quakes, volcano, eruptions, landslides, windstorm and forest fires. The impact of those natural disasters are significantly severe and affecting the quality of life of the community due to the breakdown of the public as-sets as one source to deliver public services. This paper is aimed to emphasis the importance of natural disaster risk-informed in relation to public asset management in Indonesian Central Government, particularly in asset planning stage where asset decision is made as the gate into the whole public asset management processes. A Case study in the Ministry of Finance Indonesia as the central government public asset manager and in 5 (five) line ministries/governmental agencies as public asset users was used as the approach to achieved the research objective. The case study devoured three data collection techniques i.e. interviews, observations and document archival which will be analysed by a content analysis approach. The result of the study indicates that Indonesian geographical position exposing many of public infra-structure assets as a high vulnerability to natural disasters. Information on natural-disaster trends and predictions to identify and measure the risks are available, however, such information are not utilise and integrated to the process of public infrastructure asset planning as the gate to the whole public asset management processes. Therefore, in order to accommodate and incorporate this natural disaster risk-information into public asset management processes, particularly in public asset planning, a public asset performance measurements framework should be adopted and applied in the process as one sources in making decision for infrastructure asset planning. Findings from this study provide useful input for the Ministry of Finance as public asset manager, scholars and private asset management practitioners in Indonesia to establish natural disaster risks awareness in public infrastructure asset management processes.

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In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM–test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

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Mangroves along the Sudanese Red Sea coast are under constant anthropogenic pressure. To better understand the influence of mangrove clearance on the intertidal benthic community, we investigated the composition, biodiversity and standing stock of the macrofauna communities at high-, mid- and low-water levels in three contrasting habitats: a bare sand flat, a cleared mangrove and an intact mangrove. In addition, a community-wide metric approach based on taxon-specific carbon and nitrogen isotope values was used to compare the trophic structure between the three habitats. The habitats differed significantly in terms of macrofaunal standing stock, community composition and trophic structure. The high- and mid-water levels of the intact mangroves showed a distinct macrofaunal community characterized by elevated densities and biomass, largely governed by higher decapod and gastropod abundances. Diversity was similar for cleared and intact mangroves, but much lower for the bare sand flat. Community-wide metrics indicated highest trophic diversity and community niche breadth in the intact mangroves. Differences between the cleared and intact mangroves can be partly attributed to differences in sediment characteristics resulting from mangrove clearance. These results suggest a significant impact of mangrove clearance on the macrofaunal community and trophic structure. This study calls for further investigations and management actions to protect and restore these habitats, and ensure the survival of this ecologically valuable coastal ecosystem.

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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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The objects with which the hand interacts with may significantly change the dynamics of the arm. How does the brain adapt control of arm movements to this new dynamic? We show that adaptation is via composition of a model of the task's dynamics. By exploring generalization capabilities of this adaptation we infer some of the properties of the computational elements with which the brain formed this model: the elements have broad receptive fields and encode the learned dynamics as a map structured in an intrinsic coordinate system closely related to the geometry of the skeletomusculature. The low--level nature of these elements suggests that they may represent asset of primitives with which a movement is represented in the CNS.

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This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003. Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upper-stratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) or the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models. The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is similar to 5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIAMACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.