Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis

This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.

Application of the Multivariate Prediction Method to Time Series

* This work was financially supported by RFBR-04-01-00858.

An international round-robin calibration protocol for nanoindentation measurements

Nanoindentation has become a common technique for measuring the hardness and elastic-plastic properties of materials, including coatings and thin films. In recent years, different nanoindenter instruments have been commercialised and used for this purpose. Each instrument is equipped with its own analysis software for the derivation of the hardness and reduced Young's modulus from the raw data. These data are mostly analysed through the Oliver and Pharr method. In all cases, the calibration of compliance and area function is mandatory. The present work illustrates and describes a calibration procedure and an approach to raw data analysis carried out for six different nanoindentation instruments through several round-robin experiments. Three different indenters were used, Berkovich, cube corner, spherical, and three standardised reference samples were chosen, hard fused quartz, soft polycarbonate, and sapphire. It was clearly shown that the use of these common procedures consistently limited the hardness and reduced the Young's modulus data spread compared to the same measurements performed using instrument-specific procedures. The following recommendations for nanoindentation calibration must be followed: (a) use only sharp indenters, (b) set an upper cut-off value for the penetration depth below which measurements must be considered unreliable, (c) perform nanoindentation measurements with limited thermal drift, (d) ensure that the load-displacement curves are as smooth as possible, (e) perform stiffness measurements specific to each instrument/indenter couple, (f) use Fq and Sa as calibration reference samples for stiffness and area function determination, (g) use a function, rather than a single value, for the stiffness and (h) adopt a unique protocol and software for raw data analysis in order to limit the data spread related to the instruments (i.e. the level of drift or noise, defects of a given probe) and to make the H and E r data intercomparable. © 2011 Elsevier Ltd.

2D-3D registration of CT vertebra volume to fluoroscopy projection:a calibration model assessment

This study extends a previous research concerning intervertebral motion registration by means of 2D dynamic fluoroscopy to obtain a more comprehensive 3D description of vertebral kinematics. The problem of estimating the 3D rigid pose of a CT volume of a vertebra from its 2D X-ray fluoroscopy projection is addressed. 2D-3D registration is obtained maximising a measure of similarity between Digitally Reconstructed Radiographs (obtained from the CT volume) and real fluoroscopic projection. X-ray energy correction was performed. To assess the method a calibration model was realised a sheep dry vertebra was rigidly fixed to a frame of reference including metallic markers. Accurate measurement of 3D orientation was obtained via single-camera calibration of the markers and held as true 3D vertebra position; then, vertebra 3D pose was estimated and results compared. Error analysis revealed accuracy of the order of 0.1 degree for the rotation angles of about 1mm for displacements parallel to the fluoroscopic plane, and of order of 10mm for the orthogonal displacement. © 2010 P. Bifulco et al.

Joint Densities of Correlation Coefficients for Samples from Multivariate Standard Normal Distribution

2000 Mathematics Subject Classification: 62H10.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

Large and Moderate Deviations Principles for Recursive Kernel Estimator of a Multivariate Density and its Partial Derivatives

2000 Mathematics Subject Classification: 62G07, 60F10.

Reliability-based calibration for a mechanics-based fatigue cracking design procedure

Most pavement design procedures incorporate reliability to account for design inputs-associated uncertainty and variability effect on predicted performance. The load and resistance factor design (LRFD) procedure, which delivers economical section while considering design inputs variability separately, has been recognised as an effective tool to incorporate reliability into design procedures. This paper presents a new reliability-based calibration in LRFD format for a mechanics-based fatigue cracking analysis framework. This paper employs a two-component reliability analysis methodology that utilises a central composite design-based response surface approach and a first-order reliability method. The reliability calibration was achieved based on a number of field pavement sections that have well-documented performance history and high-quality field and laboratory data. The effectiveness of the developed LRFD procedure was evaluated by performing pavement designs of various target reliabilities and design conditions. The result shows an excellent agreement between the target and actual reliabilities. Furthermore, it is clear from the results that more design features need to be included in the reliability calibration to minimise the deviation of the actual reliability from the target reliability.

Determinants of confidence and their effect on epistemic judgments: Implications for auditor calibration bias

Auditor decisions regarding the causes of accounting misstatements can have an audit effectiveness and efficiency. Specifically, overconfidence in one's decision can lead to an ineffective audit, whereas underconfidence in one's decision can lead to an inefficient audit. This dissertation explored the implications of providing various types of information cues to decision-makers regarding an Analytical Procedure task and investigated the relationship between different types of evidence cues (confirming, disconfirming, redundant or non-redundant) and the reduction in calibration bias. Information was collected using a laboratory experiment, from 45 accounting students participants. Research questions were analyzed using a 2 x 2 x 2 between-subject and within-subject analysis of covariance (ANCOVA). ^ Results indicated that presenting subjects with information cues dissimilar to the choice they made is an effective intervention in reducing the common overconfidence found in decision-making. In addition, other information characteristics, specifically non-redundant information can help in reducing a decision-maker's overconfidence/calibration bias for difficulty (compared to easy) decision-tasks. ^

The development and testing of a multivariate model of differentiation of self among Hispanics

Individuals of Hispanic origin are the nation's largest minority (13.4%). Therefore, there is a need for models and methods that are culturally appropriate for mental health research with this burgeoning population. This is an especially salient issue when applying family systems theories to Hispanics, who are heavily influenced by family bonds in a way that appears to be different from the more individualistic non-Hispanic White culture. Bowen asserted that his family systems' concept of differentiation of self, which values both individuality and connectedness, could be universally applied. However, there is a paucity of research systematically assessing the applicability of the differentiation of self construct in ethnic minority populations. ^ This dissertation tested a multivariate model of differentiation of self with a Hispanic sample. The manner in which the construct of differentiation of self was being assessed and how accurately it represented this particular ethnic minority group's functioning was examined. Additionally, the proposed model included key contextual variables (e.g., anxiety, relationship satisfaction, attachment and acculturation related variables) which have been shown to be related to the differentiation process. ^ The results from structural equation modeling (SEM) analyses confirmed and extended previous research, and helped to illuminate the complex relationships between key factors that need to be considered in order to better understand individuals with this cultural background. Overall results indicated that the manner in which Hispanic individuals negotiate the boundaries of interconnectedness with a sense of individual expression appears to be different from their non-Hispanic White counterparts in some important ways. These findings illustrate the need for research on Hispanic individuals that provides a more culturally sensitive framework. ^

The development of an optimized system of narcotic and explosive contraband mimics for calibration and training of biological detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

Headspace analysis of smokeless powders: Development of mass calibration methods using microdrop printing for chromatographic and ion mobility spectrometric detection

Smokeless powder additives are usually detected by their extraction from post-blast residues or unburned powder particles followed by analysis using chromatographic techniques. This work presents the first comprehensive study of the detection of the volatile and semi-volatile additives of smokeless powders using solid phase microextraction (SPME) as a sampling and pre-concentration technique. Seventy smokeless powders were studied using laboratory based chromatography techniques and a field deployable ion mobility spectrometer (IMS). The detection of diphenylamine, ethyl and methyl centralite, 2,4-dinitrotoluene, diethyl and dibutyl phthalate by IMS to associate the presence of these compounds to smokeless powders is also reported for the first time. A previously reported SPME-IMS analytical approach facilitates rapid sub-nanogram detection of the vapor phase components of smokeless powders. A mass calibration procedure for the analytical techniques used in this study was developed. Precise and accurate mass delivery of analytes in picoliter volumes was achieved using a drop-on-demand inkjet printing method. Absolute mass detection limits determined using this method for the various analytes of interest ranged between 0.03–0.8 ng for the GC-MS and between 0.03–2 ng for the IMS. Mass response graphs generated for different detection techniques help in the determination of mass extracted from the headspace of each smokeless powder. The analyte mass present in the vapor phase was sufficient for a SPME fiber to extract most analytes at amounts above the detection limits of both chromatographic techniques and the ion mobility spectrometer. Analysis of the large number of smokeless powders revealed that diphenylamine was present in the headspace of 96% of the powders. Ethyl centralite was detected in 47% of the powders and 8% of the powders had methyl centralite available for detection from the headspace sampling of the powders by SPME. Nitroglycerin was the dominant peak present in the headspace of the double-based powders. 2,4-dinitrotoluene which is another important headspace component was detected in 44% of the powders. The powders therefore have more than one headspace component and the detection of a combination of these compounds is achievable by SPME-IMS leading to an association to the presence of smokeless powders.

Comparative study of dissolved organic matter from groundwater and surface water in the Florida coastal Everglades using multi-dimensional spectrofluorometry combined with multivariate statistics

Dissolved organic matter (DOM) in groundwater and surface water samples from the Florida coastal Everglades were studied using excitation–emission matrix fluorescence modeled through parallel factor analysis (EEM-PARAFAC). DOM in both surface and groundwater from the eastern Everglades S332 basin reflected a terrestrial-derived fingerprint through dominantly higher abundances of humic-like PARAFAC components. In contrast, surface water DOM from northeastern Florida Bay featured a microbial-derived DOM signature based on the higher abundance of microbial humic-like and protein-like components consistent with its marine source. Surprisingly, groundwater DOM from northeastern Florida Bay reflected a terrestrial-derived source except for samples from central Florida Bay well, which mirrored a combination of terrestrial and marine end-member origin. Furthermore, surface water and groundwater displayed effects of different degradation pathways such as photodegradation and biodegradation as exemplified by two PARAFAC components seemingly indicative of such degradation processes. Finally, Principal Component Analysis of the EEM-PARAFAC data was able to distinguish and classify most of the samples according to DOM origins and degradation processes experienced, except for a small overlap of S332 surface water and groundwater, implying rather active surface-to-ground water interaction in some sites particularly during the rainy season. This study highlights that EEM-PARAFAC could be used successfully to trace and differentiate DOM from diverse sources across both horizontal and vertical flow profiles, and as such could be a convenient and useful tool for the better understanding of hydrological interactions and carbon biogeochemical cycling.

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.