Bank liquidity and the board of directors

This short paper presents the first attempt to examine empirically the relationship between the level of bank liquidity and the structure of the board of directors, in terms of board size and independence. A novel database on these board characteristics is built that includes banks operating in 10 OECD countries during the period 2000-2006. We find a negative relationship between board size and liquidity, while the impact of board independence is U-shaped. Therefore, we contend that considerations linked to these effects can have interesting implications for the design of bank conduct and for the quality of bank portfolios.Banks; Board size and independence; Liquidity risk

An application of multicriteria decision aid models in the prediction of open market share repurchases

This study presents the first attempt to develop classification models for the prediction of share repurchase announcements using multicriteria decision aid (MCDA) techniques. We use three samples consisting of 434 UK firms, 330 French firms, and 296 German firms, to develop country-specific models. The MCDA techniques that are applied for the development of the models are the UTilités Additives DIScriminantes (UTADIS) and the ELimination and Choice Expressing REality (ELECTRE) TRI. We adopt a 10-fold cross validation approach, a re-sampling technique that allows us to split the datasets in training and validation sub-samples. Thus, at the first stage of the analysis the aim is the development of a model capable of reproducing the classification of the firms considered in the training samples. Once this stage is completed, the model can be used for the classification of new firms not included in the training samples (i.e. validation stage). The results show that both MCDA models achieve quite satisfactory classification accuracies in the validation sample and they outperform both logistic regression and chance predictions. The developed models could provide the basis for a decision tool for various stakeholders such as managers, shareholders, and investment analysts

Analytical modelling of stable isotope fractionation of volatile organic compounds in the unsaturated zone

Analytical models were developed that simulate stable isotope ratios of volatile organic compounds (VOCs) near a point source contamination in the unsaturated zone. The models describe diffusive transport of VOCs, biodegradation and source ageing. The mass transport is governed by Fick's law for diffusion, and the equation for reactive transport of VOCs in the soil gas phase was solved for different source geometries and for different boundary conditions. Model results were compared to experimental data from a one-dimensional laboratory column and a radial-symmetric field experiment, and the comparison yielded a satisfying agreement. The model results clearly illustrate the significant isotope fractionation by gas-phase diffusion under transient state conditions. This leads to an initial depletion of heavy isotopes with increasing distance from the source. The isotope evolution of the source is governed by the combined effects of isotope fractionation due to vaporization, diffusion and biodegradation. The net effect can lead to an enrichment or depletion of the heavy isotope in the remaining organic phase depending on the compound and element considered. Finally, the isotope evolution of molecules migrating away from the source and undergoing degradation is governed by a combined degradation and diffusion isotope effect. This suggests that in the unsaturated zone, the interpretation of biodegradation based on isotope data must always be based on a model combining gas-phase diffusion and degradation.Comment: 11 pages, 6 figure

Binary choice models for external auditors decisions in Asian banks

Summarization: The present study investigates the efficiency of four classification techniques, namely discriminant analysis, logit analysis, UTADIS multicriteria decision aid, and nearest neighbours, in the development of classification models that could assist auditors during the examination of Asian commercial banks. To develop the auditing models and examine their classification ability, the dataset is split into two distinct samples. The training sample consists of 1,701 unqualified financial statements and 146 ones that received a qualified opinion over the period 1996–2001. The models are tested in a holdout sample of 527 unqualified financial statements and 52 ones that received a qualified opinion over the period 2002–2004. The results show that the developed auditing models can discriminate between financial statements that should receive qualified opinions from the ones that should receive unqualified opinions with an out-of-sample accuracy around 60%. The highest classification accuracy is achieved by UTADIS, followed by logit analysis, nearest neighbours and discriminant analysis. Both financial variables and the environment in which banks operate appear to be important factors.Presented on: Operational Research, An International Journa

Integrated Raw Material Approach to Sustainable Geothermal Energy Production: Harnessing CO2 for Enhanced Resource Utilization

CPG (CO2 Plume Geothermal) has recently emerged as a promising technology that combines the extraction of geothermal energy with underground CO2 storage, thus aligning with the energy objectives of Greece according to the National Energy and Climate Plan. The concept of CPG revolves around treating CO2 as a raw material, recycling it through continuous injection and production to and from a subsurface reservoir, taking advantage of the discrete plume that forms on top of the subsurface formation. As CO2 is injected, it contacts the hot formation and captures thermal energy which is eventually transferred from the reservoir to the surface facilities where it gets exploited in thermal plants. The CO2 flow system is closed thus offering the permanent storage option. Despite the favorable aspects of this technology, such as reduced energy requirements for fluid recycling, improved mobility and a smaller environmental footprint, there are also challenges that require careful consideration. CO2 is less viscous and lighter than resident brine, thus fingering effects are more prominent than sweeping displacement. As a result, CO2 breakthrough appears soon, even at wells designed for pressure maintenance through brine extraction. This highlights the need for a thorough study of the geological field and reservoir, along with the optimization of the production system’s design. This study presents a comprehensive analysis of a geothermal reservoir and covers an optimized dynamic simulation for a combined geothermal, CO2 storage and CPG system. Results demonstrate that a sustainable carbon-negative energy-producing power plant is possible. Such systems can also be implemented in already existing industries, providing a source of energy for secondary operations while also positioning the operators more strongly in the carbon tax market

Perturbation Theory and Phase Behavior Calculations Using Equation of State Models

Equations of State (EoS) live at the heart of all thermodynamic calculations in chemical engineering applications as they allow for the determination of all related fluid properties such as vapor pressure, density, enthalpy, specific heat, and speed of sound, in an accurate and consistent way. Both macroscopic EoS models such as the classic cubic EoS models as well as models based on statistical mechanics and developed by means of perturbation theory are available. Under suitable pressure and temperature conditions, fluids of known composition may split in more than one phases, usually vapor and liquid while solids may also be present, each one exhibiting its own composition. Therefore, computational methods are utilized to calculate the number and the composition of the equilibrium phases at which a feed composition will potentially split so as to estimate their thermodynamic properties by means of the EoS. This chapter focuses on two of the most pronounced EoS models, the cubic ones and those based on statistical mechanics incorporating perturbation analysis. Subsequently, it describes the existing algorithms to solve phase behavior problems that rely on the classic rigorous thermodynamics context as well as modern trends that aim at accelerating computations

Equations of state with group contribution binary interaction parameters for calculation of two-phase envelopes for synthetic and real natural gas mixtures with heavy fractions

YesThree equations of state with a group contribution model for binary interaction parameters were employed to calculate the vapor-liquid equilibria of synthetic and real natural gas mixtures with heavy fractions. In order to estimate the binary interaction parameters, critical temperatures, critical pressures and acentric factors of binary constituents of the mixture are required. The binary interaction parameter model also accounts for temperature. To perform phase equilibrium calculations, the heavy fractions were first discretized into 12 Single Carbon Numbers (SCN) using generalized molecular weights. Then, using the generalized molecular weights and specific gravities, the SCN were characterized. Afterwards, phase equilibrium calculations were performed employing a set of (nc + 1) equations where nc stands for the number of known components plus 12 SCN. The equations were solved iteratively using Newton's method. Predictions indicate that the use of binary interaction parameters for highly sour natural gas mixtures is quite important and must not be avoided. For sweet natural gas mixtures, the use of binary interaction parameters is less remarkable, however

Obtaining Parsimonious Hydraulic Conductivity Fields Using Head and Transport Observations: A Bayesian Geostatistical Parameter Estimation Approach

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained