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

Regularization and finiteness of the Lorentzian LQG vertices

We give an explicit form for the Lorentzian vertices recently introduced for possibly defining the dynamics of loop quantum gravity. As a result of so doing, a natural regularization of the vertices is suggested. The regularized vertices are then proven to be finite. An interpretation of the regularization in terms of a gauge-fixing is also given.Comment: 16 pages; Added an appendix presenting the gauge-fixing interpretation, added three references, and made some minor change

Coherent states, constraint classes, and area operators in the new spin-foam models

Recently, two new spin-foam models have appeared in the literature, both motivated by a desire to modify the Barrett-Crane model in such a way that the imposition of certain second class constraints, called cross-simplicity constraints, are weakened. We refer to these two models as the FKLS model, and the flipped model. Both of these models are based on a reformulation of the cross-simplicity constraints. This paper has two main parts. First, we clarify the structure of the reformulated cross-simplicity constraints and the nature of their quantum imposition in the new models. In particular we show that in the FKLS model, quantum cross-simplicity implies no restriction on states. The deeper reason for this is that, with the symplectic structure relevant for FKLS, the reformulated cross-simplicity constraints, in a certain relevant sense, are now \emph{first class}, and this causes the coherent state method of imposing the constraints, key in the FKLS model, to fail to give any restriction on states. Nevertheless, the cross-simplicity can still be seen as implemented via suppression of intertwiner degrees of freedom in the dynamical propagation. In the second part of the paper, we investigate area spectra in the models. The results of these two investigations will highlight how, in the flipped model, the Hilbert space of states, as well as the spectra of area operators exactly match those of loop quantum gravity, whereas in the FKLS (and Barrett-Crane) models, the boundary Hilbert spaces and area spectra are different.Comment: 21 pages; statements about gamma limits made more precise, and minor phrasing change

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

Dissociable brain mechanisms for inhibitory control: Effects of interference content and working memory capacity

In this study, event-related fMRI was used to examine whether the resolution of interference arising from two different information contents activates the same or different neuronal circuitries. In addition, we examined the extent to which these inhibitory control mechanisms are modulated by individual differences in working memory capacity. Two groups of participants with high and low working memory capacity [high span (HS) and low span (LS) participants, respectively] performed two versions of an item recognition task with familiar letters and abstract objects as stimulus materials. Interference costs were examined by means of the recent negative probe technique with otherwise identical testing conditions across both tasks. While the behavioral interference costs were of similar magnitude in both tasks, the underlying brain activation pattern differed between tasks: The object task interference-effects (higher activation in interference trials than in control trials) were restricted to the anterior intraparietal sulcus (IPS). Interference effects for familiar letters were obtained in the anterior IPS, the left postero-ventral and the right dorsolateral prefrontal cortex (PFC) as well as the precuneus. As the letters were more discernible than the objects, the results suggest that the critical feature for PFC and precuneus involvement in interference resolution is the saliency of stimulus-response mappings. The interference effects in the letter task were modulated by working memory capacity: LS participants showed enhanced activation for interference trials only, whereas for HS participants, who showed better performance and also lower interference costs in the letter task, the above-mentioned neuronal circuitry was activated for interference and control trials, thereby attenuating the interference effects. The latter results support the view that HS individuals allocate more attentional resources for the maintenance of task goals in the face of interfering information from preceding trials with familiar stimulus materials

Volatility return intervals analysis of the Japanese market

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold $q$ for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval $\tau$ and its mean $$. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.Comment: 11 page