8,023 research outputs found
A Multivariate GARCH Model with Time-Varying correlations
In this paper we propose a new multivariate GARCH model with time- varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the MLE of the varying- correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.BEKK model, constant correlation, Monte Carlo method, multivariate GARCH model, maximum likelihood estimate, varying correlation
Tests of Functional Form and Heteroscedasticity
This paper considers tests of misspecification in a heteroscedastic transformation model. We derive Lagrange multiplier (LM) statistics for (i) testing functional form and heteroscedasticity jointly, (ii) testing functional form in the presence of heteroscedasticity, and (iii) testing heteroscedasticity in the presence of data transformation. We present LM statistics based on the expected information matrix. For cases (i) and (ii), this is done assuming the Box-Cox transformation. For case (iii), the test does not depend on whether the functional form is estimated or pre-specified. Small-sample properties of the tests are assessed by Monte Carlo simulation, and comparisons are made with the likelihood ratio test and other versions of LM test. The results show that the expected-information based LM test has the most appropriate finite-sample empirical siFunctional Form, Hetersocedasticity, Lagrange Multiplier Test
Exchange-Rate Systems and Interest-Rate Behaviour: The Experience of Hong Kong and Singapore
The Currency Board System in Hong Kong and the monitoring band system in Singapore are important benchmarks for two different exchange-rate systems. In this paper we consider the implications of the two exchange-rate systems on the interest-rate behaviour of the two economies. We examine the domestic-US interest differentials under the two exchange-rate regimes during the Asian Financial Crisis as well as the pre- and post-crisis periods. Using a bivariate generalized autoregressive conditional heteroscedasticity model, we also investigate whether there is any change in the correlation between the domestic and US interest rates due to the Asian Financial Crisis.
Tests of Functional Form and Heteroscedasticity
This paper considers tests of misspecification in a heteroscedastic transformation model. We derive Lagrange multiplier (LM) statistics for (i) testing functional form and heteroscedasticity jointly, (ii) testing functional form in the presence of heteroscedasticity, and (iii) testing heteroscedasticity in the presence of data transformation. We present LM statistics based on the expected information matrix. For cases (i) and (ii), this is done assuming the Box-Cox transformation. For case (iii), the test does not depend on whether the functional form is estimated or pre-specified. Small-sample properties of the tests are assessed by Monte Carlo simulation, and comparisons are made with the likelihood ratio test and other versions of LM test. The results show that the expected-information based LM test has the most appropriate finite-sample empirical sizeFunctional Form, Heterscedasticity, Lagrange Multiplier Test
A Multivariate GARCH Model with Time-Varying Correlations
In this paper we propose a new multivariate GARCH model with time-varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we manage to construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the QMLE of the varying-correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.
Traffic congestion in interconnected complex networks
Traffic congestion in isolated complex networks has been investigated
extensively over the last decade. Coupled network models have recently been
developed to facilitate further understanding of real complex systems. Analysis
of traffic congestion in coupled complex networks, however, is still relatively
unexplored. In this paper, we try to explore the effect of interconnections on
traffic congestion in interconnected BA scale-free networks. We find that
assortative coupling can alleviate traffic congestion more readily than
disassortative and random coupling when the node processing capacity is
allocated based on node usage probability. Furthermore, the optimal coupling
probability can be found for assortative coupling. However, three types of
coupling preferences achieve similar traffic performance if all nodes share the
same processing capacity. We analyze interconnected Internet AS-level graphs of
South Korea and Japan and obtain similar results. Some practical suggestions
are presented to optimize such real-world interconnected networks accordingly.Comment: 8 page
'She has received many honours': identity in article bio statements
In contrast to the prescribed anonymity of the research article, the bio which accompanies it is perhaps the most explicit assertion of self-representation in scholarly life. Here is a rhetorical space where, in 50-100 words, authors are able to craft a narrative of expertise for themselves. It is a key opening for academics, both novice and experienced, to manage a public image through the careful recounting of achievement. Yet despite the current interest in identity, the bio has largely escaped attention. In this paper we address this neglect through analysis of 600 bios across three disciplines, exploring the importance of discipline, status and gender in mediating the ways writers claim an identity. Our argument is that, despite its brevity, the bio is an important means of representing an academic self through the recognition of collective values and membership. © 2012 Elsevier Ltd.postprin
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