Multivariate Hyper-Rotated GARCH-BEKK

For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number of parameters to cope with the ‘curse of dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal of Econometrics 179: 16–30) developed the rotated multivariate GARCH model, which focuses on the parameters for standardized variables. This paper extends the rotated multivariate GARCH model by considering a hyper-rotation, which uses a more flexible structure for the rotation matrix. The paper shows an alternative representation based on a random coefficient vector autoregressive and moving-average (VARMA) process, and provides the regularity conditions for the consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator for VARMA with hyper-rotated multivariate GARCH. The paper investigates the finite sample properties of the QML estimator for the new model. Empirical results for four exchange rate returns show the new specifications works satisfactory for reducing the number of parameters.

Optimal Neighborhood Selection for AR-ARCH Random Fields with Application to Mortality

This article proposes an optimal and robust methodology for model selection. The model of interest is a parsimonious alternative framework for modeling the stochastic dynamics of mortality improvement rates introduced recently in the literature. The approach models mortality improvements using a random field specification with a given causal structure instead of the commonly used factor-based decomposition framework. It captures some well-documented stylized facts of mortality behavior including: dependencies among adjacent cohorts, the cohort effects, cross-generation correlations, and the conditional heteroskedasticity of mortality. Such a class of models is a generalization of the now widely used AR-ARCH models for univariate processes. A the framework is general, it was investigated and illustrated a simple variant called the three-level memory model. However, it is not clear which is the best parameterization to use for specific mortality uses. In this paper, we investigate the optimal model choice and parameter selection among potential and candidate models. More formally, we propose a methodology well-suited to such a random field able to select thebest model in the sense that the model is not only correct but also most economical among all thecorrectmodels. Formally, we show that a criterion based on a penalization of the log-likelihood, e.g., the using of the Bayesian Information Criterion, is consistent. Finally, we investigate the methodology based on Monte-Carlo experiments as well as real-world datasets.

Evaluating the Three-Dimensional Printing Accuracy of Partial-Arch Models According to Outer Wall Thickness: An In Vitro Study

The printing accuracy of three-dimensional (3D) dental models using photopolymer resin affects dental diagnostic procedures and prostheses. The accuracy of research into the outer wall thickness and printing direction data for partial-arch model printing has been insufficient. This study analyzed the effects of wall thickness and printing direction accuracy. Anterior and posterior partial-arch models were designed with different outer wall thicknesses. After 3D printing, a trueness analysis was performed. Those with full-arch models were the control group. The full-arch model had an error value of 73.60 ± 2.61 µm (mean ± standard deviation). The error values for the partial-arch models with 1-, 2-, and 3-mm thick outer walls were 54.80 ± 5.34, 47.58 ± 7.59, and 42.25 ± 9.19 μm, respectively, and that for the fully filled model was 38.20 ± 4.63 μm. The printing accuracies differed significantly between 0 degrees and 60 degrees, at 49.54 ± 8.16 and 40.66 ± 6.80 μm, respectively (F = 153.121, p < 0.001). In conclusion, the trueness of the partial-arch model was better than that of the full-arch model, and models with thick outer walls at 60 degrees were highly accurate.

Estimation of Distances in 3D by Orthodontists Using Digital Models

In the field of orthodontics, digital dental arch models are increasingly replacing plaster models in orthodontic diagnostics. This change in interface from physical plaster models to digital image-based models raises the question of how orthodontists interpret intra- and inter-arch relationships from an image on a screen. In particular, the issue of the accuracy of the distances estimated on numerical models is crucial since the estimation of distances is the basis of the therapeutic decision-making process. Studies have shown that distances were well estimated on plaster models, but no study has verified this point on numerical models. This is the question that our study addresses. The experimental protocol consisted of collecting estimates of measurements made by orthodontists using digital models. The reliability of these measurements was then assessed by comparing them to the actual physical distances. We asked 31 orthodontists (19 women and 12 men; an average age of 37 years) to generate 3D model-based measurements of seven different elements: mandibular congestion, the maxillary intermolar distance, Spee’s curve, 16/26 symmetry, the right canine class, overbite, and overjet. These values were then compared to the actual measurements calculated using Insignia® software (ORMCO Corporation: Brea, CA, USA), using single sample t-tests. This test makes it possible to compare a distance estimated by the participants with a reference value, which corresponds here to the real distance. The results indicate that, overall, the distance estimates made on the 3D models differ significantly from the actual distances measured using the Insignia® software. This was particularly so for mandibular crowding (test value = 0; t (30) = 10.74; p ≤ 0.01), test value = 1; t (30) = 6.23; p ≤ 0.01). Although no study has focused on distance estimation on numerical models in the field of orthodontics, our results agree with the conclusions of studies showing that distances are not estimated in the same way in real environments and virtual environments. Additional studies will make it possible to identify more clearly the parameters (individual factors, equipment, etc.), which make it possible to improve the estimation of distances in the practice of orthodontics. In any case, these studies are necessary to improve the training of future practitioners in the use of virtual models for decision-making and to support them in the digital transition.

Comparison of Accuracy of Alginate Impression and Intraoral Scanner in Model with and without Orthodontic Brackets

Surgical splints are widely used in orthognathic surgery. The fitting of a surgical splint affects the success of the surgery. Stereolithography (STL), the method used to achieve accurate and reliable input files, is important for the manufacturing process of the surgical splint. Nowadays, data acquisition can be performed with the aid of an intraoral scanner (IOS) or impression materials. This in vitro study aimed to compare the trueness and precision of IOS (TRIOS3®, 3Shape, Copenhagen, Denmark) and alginate impression (Kromopan®, Lascod, Florence, Italy) in a full-arch dental model with/without orthodontic brackets. Custom complete arch models were fabricated with a refractive index similar to that of tooth structure. A TRIOS3® intraoral scanner (3Shape, Copenhagen, Denmark) and an alginate impression were used to duplicate the custom model without orthodontic brackets for complete arch scenarios (both upper and lower arches), n = 5. Subsequently, orthodontic brackets (Ormco®, Glendora, CA, USA) were attached to the custom model and the TRIOS® intraoral scanner and alginate impression were used again. Analysis was performed using 3-dimensional (3D) metrology software (GOM inspect®, GOM GmbH, Braunschweig, Germany) to measure surface deviations between the STL files from the custom model to evaluate and compare their trueness and precision. All data were entered into Microsoft Excel and then transferred to SPSS (Statistical Package for the Social Sciences). The average surface deviations were compared between the TRIOS3® intraoral scanner and the alginate impression using a repeated measures ANOVA (Analysis of Variance) with adjustment for multiple comparisons using Bonferroni’s correction. There were no significant differences in trueness and precision between TRIOS3® and alginate impression in full arch models with and without orthodontic brackets. Moreover, the accuracy of all groups was less than 100 microns, which was acceptable. Further in vivo studies are required to confirm these results.

Probabilistic Assessment of Monthly River Flow Discharge Using Copula And OSVR Approaches

Simulation of flow discharge based on monthly precipitation values as inputs is one of the important issues in hydrology and water resources studies, especially in areas where data with the shorter time scales are not available. In this study, the applicability of support vector regression (SVR) model optimized by Ant colony and Copula-GARCH algorithms was investigated and compared to simulate the flow discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. The correlation results of the studied paired variable confirmed the possibility of using copula-based models. The simulation results were evaluated using R2, Nash-Sutcliffe Efficiency (NSE) and root mean square error (RMSE) statistics. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE = 0.90) of Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by Copula-GARCH model compared to OSVR model in simulating the flow discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.

Distribution of Artificial Thrombi Candidates Through Patient-Specific Aortic-Arch Phantoms under Pulsatile Flow Conditions

Ischemic Stroke is the most frequent type of stroke and is subject to many studies investigating prevention means. Avoiding the difficulties and ethical problems of experimental in-vivo research, in-vitro testing is a convenient way of studying in controlled conditions the morphological impact and mechanical aspects of emboli dynamics. This in-vitro study was performed with two realistic silicone aortic-arch phantoms submitted to physiological pulsatile flow conditions. In the in-vitro test bed, using automatic image tracking and analysis, it was made possible detecting and tracking artificial spherical emboli candidates circulating in the anatomic aortic-arch models under a realistic based-patient blood flow profile. The emboli trajectories as well as their repartition in the different supra-aortic branches are presented for the two aortic-arch geometries obtained from CT scans. Through a statistical analysis performed with several artificial emboli sizes, the experimental study shows that the repartition percentages of the emboli closely follow the flowrate repartition percentages for both aortic-arch models, suggesting that higher flowrates lead to higher concentrations of emboli in a given artery. Sets of human thrombi were also injected and the repartition percentages have been established, giving the same trend as for artificial emboli.

MEASURING VOLATILITY OF NIFTY50 AND SENSEX UNDER DIFFERENT ERROR DISTRIBUTION METHODS OF E-GARCH FOR THE PERIOD BETWEEN 2011 TO 2016.

Volatility has always been a part and parcel of stock market. Understanding the volatility is very difficult though measuring it is not impossible. Choosing the right method to meausre the volatility is very crucial and important to get the reliable and accurate results. This study aims at measuring volatility of Nifty50 and Sensex under different error distribution methods of E-GARCH model. E-GARCH is one of the reliable ARCH models that measures persistent volatility and asymmetric effects. This paper bring out the best suited model for Nifty50 and Sensex in measuring the volatility under different error distribution method of E-GARCH model.

Dependence Structure Between Renminbi Movements and Volatility of Foreign Exchange Rate Returns

This article investigates the linkages of the movements in Renminbi (RMB) to volatility of exchange rate returns of other currencies before and after the yuan devaluation on 11 August 2015. A comparison between the onshore Chinese yuan (CNY) and the offshore Chinese yuan (CNH) is made. Standard regression methods underestimate the tail dependence between yuan and other exchange rate volatility, as financial data are non-normally distributed, especially when extreme event occurs. We apply Gumbel copulas to capture the presence of tail dependence between RMB returns and the volatility of exchange rate returns for 13 selected currencies, and found dependencies not revealed by the standard ARCH models. The tail dependence has increased after the RMB devaluation, suggesting that RMB depreciation is associated with higher downside risks in these currencies. This is most obvious in the currencies of Asian and ASEAN-5 countries that have strong trade and financial linkages with China. The dependence structure has shifted away from the dominance of onshore CNY rates before the devaluation to the growing importance of more volatile offshore CNH rates after the devaluation. Hence, any large depreciation in CNH will lead to a higher volatility in the other exchange rate returns, and the corresponding downside currency risks are higher than those of the CNY.