9 resultados para Monetary exchange rate model

em University of Queensland eSpace - Australia


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This paper assesses the currency risk management policies for a sample of Australian international equity trusts. The relevance of currency risk management is considered in the context of exchange rate exposure and performance measures. The study incorporates differing economic climates and particular emphasis is given to the Asian crisis in mid-1997. Our results indicate that a good proportion of funds do implement specific currency risk management policies. Furthermore, we find that for those funds managing currency risk, there is some evidence of a favourable impact on currency exposure and fund performance.

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The Euro has been used as the largest weighting element in a basket of currencies for forex arrangements adopted by several Central European countries outside the European Union (EU). The paper uses a new time-series approach to examine the relationship between the Euro exchange rate and the level of foreign reserves. It employs Zero-no-zero (ZNZ) patterned vector error-correction (VECM) modelling to investigate Granger causal relations among foreign reserves, the European Monetary Union money supply and the Euro exchange rate. The findings confirm that foreign reserves may influence movements in the Euro's exchange rate. Further, ZNZ patterned VECM modelling with exogenous variables is used to estimate the amount of foreign reserves currently required in order to again achieve a targetted Euro exchange rate

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Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

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PFG-NMR was used to study the chemical exchange of linear PHEMA having a range of molecular weights with water in DMSO containing varying quantities of water. The aim was to investigate the use of PFG-NMR to study chemical exchange between a polymer with exchangeable protons and a small fast diffusing molecule to provide insight into the conformation adopted by a polymer in solution. The experimental data were simulated closely for the two-site exchange case using the Bloch equations modified for chemical exchange and diffusion. The exchange rate could be used to detect changes in polymer conformation resulting from changes in the solvent. PHEMA of MW 10 000 showed significant time-dependent changes in exchange rate, resulting from preferential solvation of the OH sites by water, and subsequent conformational changes which altered accessibility of the OH sites to water. This behavior was not observed for larger MW PHEMA, which adopted a stable conformation immediately. Large changes in the exchange rate were not reflected in changes to the hydrodynamic radius, suggesting that a minimal overall change in the chain dimensions occurred. DMSO was found to be a poor solvent for PHEMA, which adopts a compact conformation in DMSO. This work has demonstrated that PFG-NMR is a sensitive method for detecting subtle changes in polymer conformation in polymers with exchangeable protons.

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The diagrammatic strong-coupling perturbation theory (SCPT) for correlated electron systems is developed for intersite Coulomb interaction and for a nonorthogonal basis set. The construction is based on iterations of exact closed equations for many - electron Green functions (GFs) for Hubbard operators in terms of functional derivatives with respect to external sources. The graphs, which do not contain the contributions from the fluctuations of the local population numbers of the ion states, play a special role: a one-to-one correspondence is found between the subset of such graphs for the many - electron GFs and the complete set of Feynman graphs of weak-coupling perturbation theory (WCPT) for single-electron GFs. This fact is used for formulation of the approximation of renormalized Fermions (ARF) in which the many-electron quasi-particles behave analogously to normal Fermions. Then, by analyzing: (a) Sham's equation, which connects the self-energy and the exchange- correlation potential in density functional theory (DFT); and (b) the Galitskii and Migdal expressions for the total energy, written within WCPT and within ARF SCPT, a way we suggest a method to improve the description of the systems with correlated electrons within the local density approximation (LDA) to DFT. The formulation, in terms of renormalized Fermions LIDA (RF LDA), is obtained by introducing the spectral weights of the many electron GFs into the definitions of the charge density, the overlap matrices, effective mixing and hopping matrix elements, into existing electronic structure codes, whereas the weights themselves have to be found from an additional set of equations. Compared with LDA+U and self-interaction correction (SIC) methods, RF LDA has the advantage of taking into account the transfer of spectral weights, and, when formulated in terms of GFs, also allows for consideration of excitations and nonzero temperature. Going beyond the ARF SCPT, as well as RF LIDA, and taking into account the fluctuations of ion population numbers would require writing completely new codes for ab initio calculations. The application of RF LDA for ab initio band structure calculations for rare earth metals is presented in part 11 of this study (this issue). (c) 2005 Wiley Periodicals, Inc.

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Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

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The authors measured perceptions of safety climate, motivation, and behavior at 2 time points and linked them to prior and subsequent levels of accidents over a 5-year period. A series of analyses examined the effects of top-down and bottom-up processes operating simultaneously over time. In terms of top-down effects, average levels of safety climate within groups at I point in time predicted subsequent changes in individual safety motivation. Individual safety motivation, in turn, was associated with subsequent changes in self-reported safety behavior. In terms of bottom-up effects, improvements in the average level of safety behavior within groups were associated with a subsequent reduction in accidents at the group level. The results contribute to an understanding of the factors influencing workplace safety and the levels and lags at which these effects operate.