Estimating factor models for multivariate volatilities : an innovation expansion method

We introduce an innovation expansion method for estimation of factor models for conditional variance (volatility) of a multivariate time series. We estimate the factor loading space and the number of factors by a stepwise optimization algorithm on expanding the "white noise space". Simulation and a real data example are given for illustration

Forecasting Transaction Rates: The Autoregressive Conditional Duration Model

This paper will propose a new statistical model for the analysis of data that does not arrive in equal time intervals such as financial transactions data, telephone calls, or sales data on commodities that are tracked electronically. In contrast to fixed interval analysis, the model treats the time between observation arrivals as a stochastic time varying process and therefore is in the spirit of the models of time deformation initially proposed by Tauchen and Pitts (1983), Clark (1973) and more recently discussed by Stock (1988), Lamoureux and Lastrapes (1992), Muller et al. (1990) and Ghysels and Jasiak (1994) but does not require auxiliary data or assumptions on the causes of time flow. Strong evidence is provided for duration clustering beyond a deterministic component for the financial transactions data analyzed. We will show that a very simple version of the model can successfully account for the significant autocorrelations in the observed durations between trades of IBM stock on the consolidated market. A simple transformation of the duration data allows us to include volume in the model.

Low-energy electron transport with the method of discrete ordinates

The one-dimensional discrete ordinates code ANISN was adapted to transport low energy (a few MeV) electrons. Calculated results obtained with ANISN were compared with experimental data for transmitted electron energy and angular distribution data for electrons normally incident on aluminum slabs of various thicknesses. The calculated and experimental results are in good agreement for a thin slab (0.2 of the electron range), but not for the thicker slabs (0.6 of the electron range). Calculated results obtained with ANISN were also compared with results obtained using Monte Carlo methods

Value at Risk models with long memory features and their economic performance

We study alternative dynamics for Value at Risk (VaR) that incorporate a slow moving component and information on recent aggregate returns in established quantile (auto) regression models. These models are compared on their economic performance, and also on metrics of first-order importance such as violation ratios. By better economic performance, we mean that changes in the VaR forecasts should have a lower variance to reduce transaction costs and should lead to lower exceedance sizes without raising the average level of the VaR. We find that, in combination with a targeted estimation strategy, our proposed models lead to improved performance in both statistical and economic terms

Asymptotics of 4d spin foam models

We study the asymptotic properties of four-simplex amplitudes for various four-dimensional spin foam models. We investigate the semi-classical limit of the Ooguri, Euclidean and Lorentzian EPRL models using coherent states for the boundary data. For some classes of geometrical boundary data, the asymptotic formulae are given, in all three cases, by simple functions of the Regge action for the four-simplex geometry.Comment: 10 pages, Proceedings for the 2nd Corfu summer school and workshop on quantum gravity and quantum geometry, talk given by Winston J. Fairbair

Hedgehog Pathway Activation Alters Ciliary Signaling in Primary Hypothalamic Cultures

Primary cilia dysfunction has been associated with hyperphagia and obesity in both ciliopathy patients and mouse models of cilia perturbation. Neurons throughout the brain possess these solitary cellular appendages, including in the feeding centers of the hypothalamus. Several cell biology questions associated with primary neuronal cilia signaling are challenging to address in vivo. Here we utilize primary hypothalamic neuronal cultures to study ciliary signaling in relevant cell types. Importantly, these cultures contain neuronal populations critical for appetite and satiety such as pro-opiomelanocortin (POMC) and agouti related peptide (AgRP) expressing neurons and are thus useful for studying signaling involved in feeding behavior. Correspondingly, these cultured neurons also display electrophysiological activity and respond to both local and peripheral signals that act on the hypothalamus to influence feeding behaviors, such as leptin and melanin concentrating hormone (MCH). Interestingly, we found that cilia mediated hedgehog signaling, generally associated with developmental processes, can influence ciliary GPCR signaling (Mchr1) in terminally differentiated neurons. Specifically, pharmacological activation of the hedgehog-signaling pathway using the smoothened agonist, SAG, attenuated the ability of neurons to respond to ligands (MCH) of ciliary GPCRs. Understanding how the hedgehog pathway influences cilia GPCR signaling in terminally differentiated neurons could reveal the molecular mechanisms associated with clinical features of ciliopathies, such as hyperphagia-associated obesity

Revisiting the Simplicity Constraints and Coherent Intertwiners

In the context of loop quantum gravity and spinfoam models, the simplicity constraints are essential in that they allow to write general relativity as a constrained topological BF theory. In this work, we apply the recently developed U(N) framework for SU(2) intertwiners to the issue of imposing the simplicity constraints to spin network states. More particularly, we focus on solving them on individual intertwiners in the 4d Euclidean theory. We review the standard way of solving the simplicity constraints using coherent intertwiners and we explain how these fit within the U(N) framework. Then we show how these constraints can be written as a closed u(N) algebra and we propose a set of U(N) coherent states that solves all the simplicity constraints weakly for an arbitrary Immirzi parameter.Comment: 28 page

Holomorphic Factorization for a Quantum Tetrahedron

We provide a holomorphic description of the Hilbert space H(j_1,..,j_n) of SU(2)-invariant tensors (intertwiners) and establish a holomorphically factorized formula for the decomposition of identity in H(j_1,..,j_n). Interestingly, the integration kernel that appears in the decomposition formula turns out to be the n-point function of bulk/boundary dualities of string theory. Our results provide a new interpretation for this quantity as being, in the limit of large conformal dimensions, the exponential of the Kahler potential of the symplectic manifold whose quantization gives H(j_1,..,j_n). For the case n=4, the symplectic manifold in question has the interpretation of the space of "shapes" of a geometric tetrahedron with fixed face areas, and our results provide a description for the quantum tetrahedron in terms of holomorphic coherent states. We describe how the holomorphic intertwiners are related to the usual real ones by computing their overlap. The semi-classical analysis of these overlap coefficients in the case of large spins allows us to obtain an explicit relation between the real and holomorphic description of the space of shapes of the tetrahedron. Our results are of direct relevance for the subjects of loop quantum gravity and spin foams, but also add an interesting new twist to the story of the bulk/boundary correspondence.Comment: 45 pages; published versio