Vector meson form factors and their quark-mass dependence

The electromagnetic form factors of vector mesons are calculated in an explicitly Poincar\'e covariant formulation, based on the Dyson--Schwinger equations of QCD, that respects electromagnetic current conservation, and unambiguously incorporates effects from vector meson poles in the quark-photon vertex. This method incorporates a 2-parameter effective interaction, where the parameters are constrained by the experimental values of chiral condensate and $f_{\pi}$. This approach has successfully described a large amount of light-quark meson experimental data, e.g. ground state pseudoscalar masses and their electromagnetic form factors; ground state vector meson masses and strong and electroweak decays. Here we apply it to predict the electromagnetic properties of vector mesons. The results for the static properties of the $\rho$-meson are: charge radius $= 0.54 {\rm fm}^2$, magnetic moment $\mu = 2.01$, and quadrupole moment ${\cal Q} = -0.41$. We investigate the quark mass dependence of these static properties and find that our results at the charm quark mass are in agreement with recent lattice simulations. The charge radius decreases with increasing quark mass, but the magnetic moment is almost independent of the quark mass.Comment: 13 pages, 7 figure

Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model

This paper develops a matrix-variate adaptive Markov chain Monte Carlo (MCMC) methodology for Bayesian Cointegrated Vector Auto Regressions (CVAR). We replace the popular approach to sampling Bayesian CVAR models, involving griddy Gibbs, with an automated efficient alternative, based on the Adaptive Metropolis algorithm of Roberts and Rosenthal, (2009). Developing the adaptive MCMC framework for Bayesian CVAR models allows for efficient estimation of posterior parameters in significantly higher dimensional CVAR series than previously possible with existing griddy Gibbs samplers. For a n-dimensional CVAR series, the matrix-variate posterior is in dimension $3n^2 + n$, with significant correlation present between the blocks of matrix random variables. We also treat the rank of the CVAR model as a random variable and perform joint inference on the rank and model parameters. This is achieved with a Bayesian posterior distribution defined over both the rank and the CVAR model parameters, and inference is made via Bayes Factor analysis of rank. Practically the adaptive sampler also aids in the development of automated Bayesian cointegration models for algorithmic trading systems considering instruments made up of several assets, such as currency baskets. Previously the literature on financial applications of CVAR trading models typically only considers pairs trading (n=2) due to the computational cost of the griddy Gibbs. We are able to extend under our adaptive framework to $n >> 2$ and demonstrate an example with n = 10, resulting in a posterior distribution with parameters up to dimension 310. By also considering the rank as a random quantity we can ensure our resulting trading models are able to adjust to potentially time varying market conditions in a coherent statistical framework.Comment: to appear journal Bayesian Analysi

Bayesian Cointegrated Vector Autoregression models incorporating Alpha-stable noise for inter-day price movements via Approximate Bayesian Computation

We consider a statistical model for pairs of traded assets, based on a Cointegrated Vector Auto Regression (CVAR) Model. We extend standard CVAR models to incorporate estimation of model parameters in the presence of price series level shifts which are not accurately modeled in the standard Gaussian error correction model (ECM) framework. This involves developing a novel matrix variate Bayesian CVAR mixture model comprised of Gaussian errors intra-day and Alpha-stable errors inter-day in the ECM framework. To achieve this we derive a novel conjugate posterior model for the Scaled Mixtures of Normals (SMiN CVAR) representation of Alpha-stable inter-day innovations. These results are generalized to asymmetric models for the innovation noise at inter-day boundaries allowing for skewed Alpha-stable models. Our proposed model and sampling methodology is general, incorporating the current literature on Gaussian models as a special subclass and also allowing for price series level shifts either at random estimated time points or known a priori time points. We focus analysis on regularly observed non-Gaussian level shifts that can have significant effect on estimation performance in statistical models failing to account for such level shifts, such as at the close and open of markets. We compare the estimation accuracy of our model and estimation approach to standard frequentist and Bayesian procedures for CVAR models when non-Gaussian price series level shifts are present in the individual series, such as inter-day boundaries. We fit a bi-variate Alpha-stable model to the inter-day jumps and model the effect of such jumps on estimation of matrix-variate CVAR model parameters using the likelihood based Johansen procedure and a Bayesian estimation. We illustrate our model and the corresponding estimation procedures we develop on both synthetic and actual data.Comment: 30 page

Scaling analysis of FLIC fermion actions

The Fat Link Irrelevant Clover (FLIC) fermion action is a variant of the $O(a)$-improved Wilson action where the irrelevant operators are constructed using smeared links. While the use of such smearing allows for the use of highly improved definitions of the field strength tensor $F_{\mu\nu},$ we show that the standard 1-loop clover term with a mean field improved coefficient $c_{\rm sw}$ is sufficient to remove the $O(a)$ errors, avoiding the need for non-perturbative tuning. This result enables efficient dynamical simulations in QCD with the FLIC fermion action.Comment: 5 pages, 3 figure

Pseudoscalar and vector meson form factors from lattice QCD

We present a study of the pseudoscalar and vector meson form factors, calculated using the Fat-Link Irrelevant Clover (FLIC) action in the framework of Quenched Lattice QCD. Of particular interest is the determination of a negative quadrupole moment, indicating that the $\rho$ meson is not spherically symmetric.Comment: 11 pages, 15 figures, 9 table

Isolating the Roper Resonance in Lattice QCD

We present results for the first positive parity excited state of the nucleon, namely, the Roper resonance ($N^{{{1/2}}^{+}}$=1440 MeV) from a variational analysis technique. The analysis is performed for pion masses as low as 224 MeV in quenched QCD with the FLIC fermion action. A wide variety of smeared-smeared correlation functions are used to construct correlation matrices. This is done in order to find a suitable basis of operators for the variational analysis such that eigenstates of the QCD Hamiltonian may be isolated. A lower lying Roper state is observed that approaches the physical Roper state. To the best of our knowledge, the first time this state has been identified at light quark masses using a variational approach.Comment: 7pp, 4 figures; minor typos corrected and one Ref. adde