A multiplicative model for volume and volatility

We first present prima facie evidence for the predictions generated by the mixture of distributions hypothesis, using daily German stock returns and their corresponding daily trading volumes and number of trades. These last two variables are used as proxies for the stochastic rate of information arrival when one wishes to explain GARCH effects by adhering to the mixture of distributions hypothesis. We show that there is no need for these proxies when the stochastic rate of information arrival follows an inverted gamma distribution. Daily trading volume and the daily number of trades, however, empirically provide an explanation for the occurrence of conditional heteroskedasticity of the GARCH form. We estimate several specifications where daily trading volume is included in the conditional variance equation additively and multiplicatively. The new multiplicative specification clearly outperforms the additive specification.     

Estimating and Visualizing Conditional Densities

Abstract

We consider the kernel estimator of conditional density and derive its asymptotic bias, variance, and mean-square error. Optimal bandwidths (with respect to integrated mean-square error) are found and it is shown that the convergence rate of the density estimator is order n ^–2/3. We also note that the conditional mean function obtained from the estimator is equivalent to a kernel smoother. Given the undesirable bias properties of kernel smoothers, we seek a modified conditional density estimator that has mean equivalent to some other nonparametric regression smoother with better bias properties. It is also shown that our modified estimator has smaller mean square error than the standard estimator in some commonly occurring situations. Finally, three graphical methods for visualizing conditional density estimators are discussed and applied to a data set consisting of maximum daily temperatures in Melbourne, Australia.     

Adaptive frame methods for elliptic operator equations: the steepest descent approach

Massimo Fornasier^¶ Dipartimento di Metodi e Modelli Matematici per le Scienze Applicate, Università "La Sapienza" in Roma, Via Antonio Scarpa, 16/B, I-00161 Roma, Italy Rob Stevenson^|| Department of Mathematics, Utrecht University, PO Box 80.010, NL-3508 TA Utrecht, The Netherlands ^{This paper is concerned with the development of adaptive numericalmethods for elliptic operator equations. We are particularlyinterested in discretization schemes based on wavelet frames.We show that by using three basic subroutines an implementable,convergent scheme can be derived, which, moreover, has optimalcomputational complexity. The scheme is based on adaptive steepestdescent iterations. We illustrate our findings by numericalresults for the computation of solutions of the Poisson equationwith limited Sobolev smoothness on intervals in 1D and L-shapeddomains in 2D.}     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Extracting metabolite ions out of a matrix background by combined mass defect,neutral loss and isotope filtration

Mass defect, neutral loss and isotope filtration techniques were applied to electrospray ionization mass spectrometry (ESI‐MS) data obtained for in vivo and in vitro samples of drug metabolism studies. A combination of these post‐acquisition processing techniques was shown to be more powerful than the use of one of these tools alone for the detection in complex matrices of metabolites of candidate drugs with a characteristic isotope pattern (e.g. containing bromine, chlorine, or a high proportion of radiolabeled drug (¹²C/¹⁴C)) or characteristic neutral losses. In combination with ‘all‐in‐one’ data acquisition this methodology is able to perform software‐driven constant neutral loss scanning for an unlimited number of mass differences at any time after analysis. Highly selective MS chromatograms were obtained with excellent correlation with their corresponding radiochromatograms. Copyright © 2009 John Wiley & Sons, Ltd.     

Numerical Modeling of Solitons in a Low Birefringent Optical Fiber

A numerical investigation, based on the split-step Fourier transform algorithm of all optical switching of solitons in a low birefringent optical fiber is presented. The numerical algorithm is described in detail. This revised version was published online in August 2006 with corrections to the Cover Date.     

Micro-fabricated metal nozzle plates used for water-in-oil and oil-in-water emulsification

In this paper the fabrication and use of micro-structured metal nozzle plates as emulsification devices is investigated and discussed. These structured metal nozzle plates were fabricated via two distinct routes. Laser ablation, performed with a femtosecond laser, was used to drill micrometer-sized holes into stainless steel and aluminum foils. Also a conventional steel mesh with an average pore size of 2.4 μm fabricated by weaving and roll compaction of micrometer-sized steel wires was investigated. The perforated metal nozzle plates were used for oil-in-water and after hydrophobization with alkylchlorosilanes for water-in-oil emulsification as well. In both cases, two types of drop formation processes were observed. The first one is the shear-induced drop formation well known for cross-flow membrane emulsification. The second is the spontaneous drop formation known from microchannel emulsification.     

The European way to go: Virtual Central Laboratory

In clinical pharmaceutical trials often one central laboratory is used for the analysis of routine parameters, the so-called safety parameters. In many countries the heads of laboratory departments question the quality of such analysis in terms of quality of samples after transport, continuity of patient related medical laboratory information before, during and after the trial; turn around time; alerting procedures and consultancy to requesting physicians. On the other hand, the pharmaceutical industry prefers to work with central laboratories since they can claim certification or accreditation. Also the use of one set of reference values is an important issue, as well as electronic data transfer to the trial organizer's database. The concept of a Virtual Central Laboratory (VCL), initiated in the Netherlands, tries to solve this conflicting situation. In the concept, local hospital laboratories receive computer-assisted aid in the identification of patients, trials, visits and requests. The laboratory data are transformed using calibrator sets to produce a homogeneous data set across laboratories, resulting in one set of reference values. The data are electronically transferred to a central computer from which they are send in any desired format to the trial organizer's database. Participating laboratories are obliged to work towards accreditation. The VCL acts as a central counterpart for both the pharmaceutical industry and local laboratories. The concept offers advantages to the pharmaceutical industry, the investigator and local laboratories.     

Boundary value problems for Yang—Mills fields

This paper investigates boundary value problems for Hermitian Yang—Mills equations over complex manifolds. The main result is the unique solubility of the Dirichlet problem for the Hermitian Yang—Mills equation. Connections with a number of topics are found, including the link with loop groups.