Process scale high performance liquid chromatography. Part III: Optimization procedure and economics of silica matrices

Summary An analytical procedure to optimise the solvent system for a given high-performance liquid chromatographic (HPLC) separation is described; it also distinguishes any preference between normal and reversed phase systems. These results can be applied directly to process scale HPLC. If intermediate pure samples are required a feasibility study and a proving trial continue the assessment. Support lifetime, cycle time, yield and purity are assessed practically and from this information processing costs can be calculated. Typical costs are given based upon reasonable assumptions. This work was conducted in the Chemical Technology Unit, University of Manchester Institute of Science and Technology, P. O. Box 88, Manchester M60 1QD, U.K.     

Portfolio optimization with short-selling and spin-glass

In this paper, we solve a general problem of optimizing a portfolio in a futures markets framework, extending the previous work of Galluccio et al. [Physica A 259, 449 (1998)]. We allow for long buying/short selling of a relatively large number of assets, assuming a fixed level of margin requirement. Because of non-linearity in the constraint, we derive a multiple equilibrium solution, in a size exponential respect to the number of assets. That means that we can not obtain the unique efficiency frontier, but many of them and each one is related to different levels of risk. Such a problem is analogous to that of finding the ground state in long-ranged Ising spin glass with external field. In order to get the best portfolio (i.e. that is along the best efficiency frontier), we have to implement a two-step procedure, performing the exhaustive enumeration of all local minima. We develop a concrete application, where the different part of the proposed solution are computed. Received 31 December 2001     

Choosing regulatory options when environmental costs are uncertain

An optimal regulatory regime is explored in which regulating a non-degradable pollution stock, e.g., the accumulation of greenhouse gases (GHGs) in the atmosphere, would be based on a model of optimal statistical decisions where it is shown when it pays to ‘act and learn’ and when to ‘learn and act’. The value of information in reducing uncertainty can be shown to be sensitive to accuracy and likelihood of scientific research results. Some interesting policy results are obtained for the dynamic intertemporal decision situation when the value of new information is an outcome of stochastic optimization with learning.     

Adaptive use of technical indicators for the prediction of intra-day stock prices

We examine the effectiveness of frequently used technical indicators for intra-day forecast by applying them on the tick data of various stock prices. We show that the optimal combination of a few indicators chosen for each stock by using evolutional computation provides us a good forecast on the level of the future price at several ticks ahead.     

Statistical equilibrium in simple exchange games II. The redistribution game

We propose a simple stochastic exchange game mimicking taxation and redistribution. There are g agents and n coins; taxation is modeled by randomly extracting some coins; then, these coins are redistributed to agents following Polya's scheme. The individual wealth equilibrium distribution for the resulting Markov chain is the multivariate symmetric Polya distribution. In the continuum limit, the wealth distribution converges to a Gamma distribution, whose form factor is just the initial redistribution weight. The relationship between this taxation-and-redistribution scheme and other simple conservative stochastic exchange games (such as the BDY game) is discussed.     

Large dimension forecasting models and random singular value spectra

We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval where singular values are expected in the absence of any true correlations between the variables under study. Our result can be seen as the natural generalization of the Marčenko-Pastur distribution for the case of rectangular correlation matrices. We illustrate the interest of our method on a set of macroeconomic time series.     

Chapter 1 Introduction: Extensions and new developments in DEA

The extensions, new developments and new interpretations for DEA covered in this paper include: (1) new measures of efficiency, (2) new models and (3) new ways of implementing established models with new results and interpretations presented that include treatments of congestion, returns-to-scale and mix and technical inefficiencies and measures of efficiency that can be used to reflect all pertinent properties. Previously used models, such as those used to identify allocative inefficiencies, are extended by means of assurance region approaches which are less demanding in their information requirements and underlying assumptions. New opportunities for research are identified in each section of this chapter. Sources of further developments and possible sources for further help are also suggested with references supplied to other papers that appear in this volume and which are summarily described in this introductory chapter.     

Ab initio calculation of the dipole moment function of hydrogen iodide

SCEP/CEPA and MC SCF potential energy and dipole moment functions for hydrogen iodide have been calculated. Spectroscopic constants and vibrational dipole matrix elements obtained from the CEPA functions are in good agreement with experimental data. In contrast to previous results for hydrogen fluoride, the MC SCF dipole moment function is less accurate than the CEPA function.     

Decomposing technical efficiency and scale elasticity in two-stage network DEA

The constant returns to scale assumption maintained by neoclassical theorists for justifying the black-box structure of production technology in long run does not necessarily allow one to infer that there are no scale benefits available in its sub-technologies. Most of real-life production technologies are multi-stage in nature, and the sources of increasing returns lie in the sub-technologies. It is, therefore, imperative to estimate the scale economies of a firm not only for the network technology but also for the sub-technologies. To accomplish this, two approaches are suggested in this contribution, based on the premise concerning whether a network technology construct considers allocative inefficiency. The first approach, which is ours, makes use of a single network technology for two interdependent sub-technologies. The second approach, which is due to Kao and Hwang (2011), however, assumes complete allocative efficiency by considering two independent sub-technology frontiers, one for each sub-technology. The distinction between these two approaches is important from a policy point of view since the network efficiencies revealed from these two approaches have distinctive causative factors that do not permit them to be used interchangeably.