A New Dynamic Mixture Copula Mechanism to Examine the Nonlinear and Asymmetric Tail Dependence Between Stock and Exchange Rate Returns

This paper develops a new time-varying mixture copula, in which the dynamic weights of four distinct copulas are determined by a two-stratum process, to investigate the magnitude of tail dependence in four independent quadrants. In the two-stratum process, the weight of each copula is determined firstly by the relative importance of positive and negative dependence structures, and then by its own past values and adjustment processes. The weighting mechanism is time-varying in each stratum. This new specification is applied to analyze the asymmetric tail dependencies between the stock and exchange rate markets. Empirical results show four interesting findings. First, the quasi-maximum likelihood estimation (QMLE) has a better fitting ability than does the inference function for margins. The relative efficiency of the QMLE is irrespective of marginal specifications. Second, the goodness-of-fit tests of the new time-varying mixture copula are crucially affected by the marginal specifications. Third, estimation methods impact mixture weights. Four distinct tail dependencies are observed, revealing the importance of considering all four tails concurrently, and not just parts of the four tails. Fourth, the asymmetric positive and negative dependencies are significant. Each country shows a similar pattern of asymmetric negative dependence, but a different pattern of asymmetric positive dependence. These empirical findings provide important portfolio allocation implications.

     

Spatial Temporal Dynamics and Molecular Evolution of Re-Emerging Rabies Virus in Taiwan

Taiwan has been recognized by the World Organization for Animal Health as rabies-free since 1961. Surprisingly, rabies virus (RABV) was identified in a dead Formosan ferret badger in July 2013. Later, more infected ferret badgers were reported from different geographic regions of Taiwan. In order to know its evolutionary history and spatial temporal dynamics of this virus, phylogeny was reconstructed by maximum likelihood and Bayesian methods based on the full-length of glycoprotein (G), matrix protein (M), and nucleoprotein (N) genes. The evolutionary rates and phylogeographic were determined using Beast and SPREAD software. Phylogenetic trees showed a monophyletic group containing all of RABV isolates from Taiwan and it further separated into three sub-groups. The estimated nucleotide substitution rates of G, M, and N genes were between 2.49 × 10⁻⁴–4.75 × 10⁻⁴ substitutions/site/year, and the mean ratio of dN/dS was significantly low. The time of the most recent common ancestor was estimated around 75, 89, and 170 years, respectively. Phylogeographic analysis suggested the origin of the epidemic could be in Eastern Taiwan, then the Formosan ferret badger moved across the Central Range of Taiwan to western regions and separated into two branches. In this study, we illustrated the evolution history and phylogeographic of RABV in Formosan ferret badgers.     

Assessing the characteristics of groundwater quality of arsenic contaminated aquifers in the blackfoot disease endemic area

Redox couples approach and multivariate statistical techniques, including factor analysis, cluster analysis and discriminant analysis, were applied to evaluate and to interpret the complex groundwater quality in the blackfoot disease endemic area, Taiwan. Most groundwater samples were characterized as Na-Ca-HCO(3) with HCO(3)(-) as the dominant anion. Total arsenic (As) concentration, predominantly as As(3+), ranged from <1.0 to 562.7 μg/L. The patterns of measured reducing potential were consistent with those values calculated from As couple, revealing the in situ environment enhanced the accumulation of As concentration in the groundwater. Factor analysis proposed a four-factor model, comprising salination, reductive dissolution of Fe/Mn oxyhydroxides, As reduction and chemical potential factor, and explained 89.94% of total variance in groundwater. Furthermore, two factors, reductive dissolution of Fe/Mn oxyhydroxides and As reduction, suggested that the decoupled reductive processes accounted for high As concentration in this area. Cluster analysis was adopted to spatially categorize the sampled wells into three main clusters and characterized by the factor scores of the four-factor model. Two-parameter (pH and Eh) model derived from discriminant analysis can be used for preliminary assessment to determine whether the As concentration exceeds 10 μg/L with simple field measurements in this area.