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.

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

An Optimal and Distributed Method for Voltage Regulation in Power Distribution Systems

This paper addresses the problem of voltage regulation in power distribution networks with deep-penetration of distributed energy resources, e.g., renewable-based generation, and storage-capable loads such as plug-in hybrid electric vehicles. We cast the problem as an optimization program, where the objective is to minimize the losses in the network subject to constraints on bus voltage magnitudes, limits on active and reactive power injections, transmission line thermal limits and losses. We provide sufficient conditions under which the optimization problem can be solved via its convex relaxation. Using data from existing networks, we show that these sufficient conditions are expected to be satisfied by most networks. We also provide an efficient distributed algorithm to solve the problem. The algorithm adheres to a communication topology described by a graph that is the same as the graph that describes the electrical network topology. We illustrate the operation of the algorithm, including its robustness against communication link failures, through several case studies involving 5-, 34-, and 123-bus power distribution systems.Comment: To Appear in IEEE Transaction on Power System

A Framework for the Implementation of RFID Systems

There are an increasing number of organizations planning to implement Radio Frequency Identification (RFID) systems to enhance their competitiveness. Due to the novelty of the technology, many managerial challenges exist in determining and planning for the implementation of such systems. These challenges often lead to wasted efforts and resources, as well as to failed implementations. This paper presents a systematic and holistic RFID implementation framework which has been validated by both users and experts. The framework outlines the important tasks to be performed in each step of the implementation process. To enable practitioners to make informed go/no‐go decisions, essential considerations of implementation are also discussed in this paper. Furthermore, the critical success factors for the deployment of such systems are also elaborated

A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model with Time-Varying Correlations

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Analysis of telephone network traffic based on a complex user network

The traffic in telephone networks is analyzed in this paper. Unlike the classical traffic analysis where call blockings are due to the limited channel capacity, we consider here a more realistic cause for call blockings which is due to the way in which users are networked in a real-life human society. Furthermore, two kinds of user network, namely, the fully-connected user network and the scale-free network, are employed to model the way in which telephone users are connected. We show that the blocking probability is generally higher in the case of the scale-free user network, and that the carried traffic intensity is practically limited not only by the network capacity but also by the property of the user network.Comment: 17 pages, 9 figures, accepted for Physica

Isoprenoid biosynthesis via the methylerythritol phosphate pathway: the (E)-4-hydroxy-3-methylbut-2-enyl diphosphate reductase (LytB/IspH) from Escherichia coli is a [4Fe–4S] protein

AbstractThe last enzyme (LytB) of the methylerythritol phosphate pathway for isoprenoid biosynthesis catalyzes the reduction of (E)-4-hydroxy-3-methylbut-2-enyl diphosphate into isopentenyl diphosphate and dimethylallyl diphosphate. This enzyme possesses a dioxygen-sensitive [4Fe–4S] cluster. This prosthetic group was characterized in the Escherichia coli enzyme by UV/visible and electron paramagnetic resonance spectroscopy after reconstitution of the purified protein. Enzymatic activity required the presence of a reducing system such as flavodoxin/flavodoxin reductase/reduced nicotinamide adenine dinucleotide phosphate or the photoreduced deazaflavin radical

Attack Resilience of the Evolving Scientific Collaboration Network

Stationary complex networks have been extensively studied in the last ten years. However, many natural systems are known to be continuously evolving at the local (“microscopic”) level. Understanding the response to targeted attacks of an evolving network may shed light on both how to design robust systems and finding effective attack strategies. In this paper we study empirically the response to targeted attacks of the scientific collaboration networks. First we show that scientific collaboration network is a complex system which evolves intensively at the local level – fewer than 20% of scientific collaborations last more than one year. Then, we investigate the impact of the sudden death of eminent scientists on the evolution of the collaboration networks of their former collaborators. We observe in particular that the sudden death, which is equivalent to the removal of the center of the egocentric network of the eminent scientist, does not affect the topological evolution of the residual network. Nonetheless, removal of the eminent hub node is exactly the strategy one would adopt for an effective targeted attack on a stationary network. Hence, we use this evolving collaboration network as an experimental model for attack on an evolving complex network. We find that such attacks are ineffectual, and infer that the scientific collaboration network is the trace of knowledge propagation on a larger underlying social network. The redundancy of the underlying structure in fact acts as a protection mechanism against such network attacks

Treatment outcome and prognostic factor analysis in transplant-eligible Chinese myeloma patients receiving bortezomib-based induction regimens including the staged approach, PAD or VTD

BACKGROUND: We have reported promising outcomes using a staged approach, in which bortezomib/thalidomide/dexamethasone was used only in 14 patients with suboptimal response to VAD (vincristine/adriamycin/dexamethasone) before autologous stem cell transplantation (ASCT). Here we compared the outcomes of the staged approach with frontline PAD (bortezomib/doxorubicin/dexamethasone) or VTD (bortezomib/thalidomide/dexamethasone) induction, and analysed prognostic factors for outcome. PATIENTS AND METHODS: Ninety-one transplant-eligible Chinese patients received three induction regimens prior to ASCT [staged approach (N = 25), PAD (N = 31), VTD (N = 35)]. and received thalidomide maintenance for 2 years post-ASCT. RESULTS: 43 (47.3%) patients had International Staging System (ISS) III disease. By an intention-to-treat analysis, the overall CR/nCR rate were 37.4% post-induction, and 62.6% post-ASCT. Five-year overall (OS) and event-free (EFS) survivals were 66% and 45.1%. There was no difference of the post-induction CR/nCR rate, EFS or OS between patients induced by these three regimens. Moreover, ISS III disease did not affect CR/nCR rates. Multivariate analysis showed that ISS and post-ASCT CR/nCR impacted OS while ISS and post-induction CR/nCR impacted EFS. CONCLUSIONS: These three induction regimens produced comparable and favorable outcomes in myeloma. The unfavorable outcome of ISS stage III persisted despite upfront/early use of bortezomib. CR/nCR predicted favorable survivals