A robust nonparametric approach to evaluate and explain the performance of mutual funds

The topic of the measurement of mutual funds’ performance is receiving an increasing interest both from an applied and a theoretical perspective. Beside the traditional financial literature, a growing body of studies has started to apply the tools of frontier analysis for benchmarking comparisons in portfolio analysis. Our paper contributes to this literature proposing a robust nonparametric approach for analysing mutual funds. It is based on the concept of order-m frontier [Cazals, C., Florens, J.P., Simar, L., 2002. Nonparametric frontier estimation: A robust approach. Journal of Econometrics 106, 1–25] and on a probabilistic approach [Daraio, C., Simar, L., 2005. Introducing environmental variables in nonparametric frontier models: A probabilistic approach. Journal of Productivity Analysis 24 (1), 93–121] to find out the factors explaining mutual funds’ performance. Within this framework, a decomposition of conditional efficiency is proposed, and its usefulness for economic interpretation analysed. Our approach is illustrated by using US mutual funds data, grouped for category by objective. Economies of scale, slacks and market risks are investigated. A comparison of traditional, nonparametric and robust performance measures is also offered.     

A mechanical approach to explain cortical folding phenomena in healthy and diseased brains

The development of the human brain with its characteristically folded surface morphology remains an intensively discussed topic. Impressive advancements in different fields of research have enhanced the understanding of the brain. However, the mechanism that underlies the folding process in healthy and diseased brains remains undetermined. Here, we hypothesize that growth induced mechanical instabilities drive folding. Using the nonlinear field theories of continuum mechanics supplemented by the theory of finite growth [1], we model the human brain as a bi-material with the cerebral cortex, a morphogenetically growing outer layer of gray matter, and the subcortex, a strain-driven growing inner core of white matter [2]. This approach integrates the two popular but competing hypotheses that cortical folding is either driven by differential growth or by axon elongation. Through systematic sensitivity analyses, we identify the critical process parameters of cortical folding and quantify their impact on brain morphology. We further simulate phenomena causing malformations like lissencephaly and polymicrogyria [3], which are associated with neurological disorders, including severe retardation, epilepsy, schizophrenia, and autism. Understanding the mechanisms of cortical folding during brain development might facilitate the diagnostics and treatment of malformed brains. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A heuristic decomposition approach to optimal control in a water supply model

The optimal pump control problem in a water supply system can be formulated as a mixed integer programming problem. In general, this problem is very difficult to solve by conventional integer programming algorithms, because the number of decision variables is as large as the total number of combinations of pump stations and control periods. However, it possesses a certain block triangular structure, which offers an attractive computational scheme. Taking advantage of this structure, this paper proposes a heuristic decomposition algorithm for finding a good feasible solution to this type of mixed integer programming problems. Numerical results for an actual pump control problem are also reported.     

A phase field approach to solidification and solute separation in water solutions

We propose a phase field model for the solid–liquid phase transition in a water-salt (sodium chloride) solution in the absence of macroscopic motion, under possibly non-isothermal conditions. A thermodynamic approach based on a free energy functional is assumed. The model consists of three evolution equations: a time-dependent Ginzburg–Landau equation for the solid–liquid phase change, a diffusion equation of the Cahn–Hilliard kind for the solute dynamics and the heat equation for the temperature change. The proposed system is aimed to contribute to the modelling of the brine channels formation in the ice of the polar seas.     

A continuous approach to combinatorial optimization: application of water system pump operations

In this paper, we have suggested a penalty method to modify the combinatorial optimization problem with the linear constraints to a global optimization problem with linear constraints. It also deals with a topic of vital significance of pump operation optimization in a water system. In this connection we have done a lot of work to formulate a model based on a simplified flow volume balance to resolve the problem of optimal pump operation settings of switching “ON” and “OFF” with the reduced gradient method. This global solution approach incorporates some benefits for practical application to a real system as is shown in the case study.     

A bilinear approach to cone multipliers II. Applications

This paper is a continuation of [TV], in which new bilinear estimates for surfaces in were proven. We give a concrete improvement to the square function estimate of Mockenhaupt [M]. We apply these estimates to give new progress on several open problems concerning the wave and Schr?dinger equation in , and convolution with curves in . Submitted: September 1998, Revised version: January 1999.     

A novel hydrodynamic approach to superconductivity. Appearance of the Meissner effect

From the point of view of spin interactions, considering the electron a charged quantised vortex-type object (QVTO) with vortex strength Γ=±h/2m, we study a two-dimensional system of electrons with antiferromagnetic arrangement of spins. In the conditions of an applied magnetic field some of the electrons will flip the spin and the equivalent QVTO system will start to move due to corroborated action of the vortex population. The developed currents will create a magnetic field opposed to the applied magnetic field, leading to the appearance of Meissner effect. As a function of the intrinsic pinning, the velocity field yields two behaviours, identified with Type I and Type II superconductors. The critical values of the magnetic field arise naturally from the balance between the Lorentz and Coulombian forces acting upon a moving QVTO. A temperature dependence of the distance between the QVTO and critical field is derived.     

A Lagrangian decomposition approach for the pump scheduling problem in water networks

Dynamic pricing has become a common form of electricity tariff, where the price of electricity varies in real time based on the realized electricity supply and demand. Hence, optimizing industrial operations to benefit from periods with low electricity prices is vital to maximizing the benefits of dynamic pricing. In the case of water networks, energy consumed by pumping is a substantial cost for water utilities, and optimizing pump schedules to accommodate for the changing price of energy while ensuring a continuous supply of water is essential. In this paper, a Mixed-Integer Non-linear Programming (MINLP) formulation of the optimal pump scheduling problem is presented. Due to the non-linearities, the typical size of water networks, and the discretization of the planning horizon, the problem is not solvable within reasonable time using standard optimization software. We present a Lagrangian decomposition approach that exploits the structure of the problem leading to smaller problems that are solved independently. The Lagrangian decomposition is coupled with a simulation-based, improved limited discrepancy search algorithm that is capable of finding high quality feasible solutions. The proposed approach finds solutions with guaranteed upper and lower bounds. These solutions are compared to those found by a mixed-integer linear programming approach, which uses a piecewise-linearization of the non-linear constraints to find a global optimal solution of the relaxation. Numerical testing is conducted on two real water networks and the results illustrate the significant costs savings due to optimizing pump schedules.     

A knowledge-based approach to scheduling in an F.M.S.

This paper reports the development of a computer-based system for production scheduling in a dedicated FMS. The system is based on the state-operator framework commonly used in artificial intelligence. Such a system consists of three components: (i) a knowledge base of states, which describes both the current task domain situation and the goal to be achieved; (ii) a set of operators that are used to manipulate the knowledge base; and (iii) a control strategy to decide which operators to apply next and to resolve conflicts. Some of the interesting features of the scheduling system include: (i) the ability to detect resource conflicts; (ii) the ability to determine alternate routes for a given part in the event of a resource conflict; and (iii) the ability to amend plans if an alternate route is found. These features allow the system to take advantage of the flexible routing for parts that an FMS allows. The system has been implemented using the XLISP programming language. Implementation considerations are discussed. A small but comprehensive example is presented. Further research directions are suggested.     

Nonparametric recursive estimation of the derivative of the regression function with application to sea shores water quality

This paper is devoted to the nonparametric estimation of the derivative of the regression function in a nonparametric regression model. We implement a very efficient and easy to handle statistical procedure based on the derivative of the recursive Nadaraya–Watson estimator. We establish the almost sure convergence as well as the asymptotic normality for our estimates. We also illustrate our nonparametric estimation procedure on simulated data and real life data associated with sea shores water quality and valvometry.

     

A fuzzy inexact two-phase programming approach to solving optimal allocation problems in water resources management

Inappropriate agricultural activities are the main reasons of water shortage and environmental pollution in many rural areas. How to generate preferred decision schemes for agricultural activities is a critical issue for decision makers. In this study, a two-phase programming approach is advanced for regional water resources allocation in a rural region of China. The approach shows applicability when the uncertain inputs are provided as intervals and such uncertainty is desired to be delivered to the corresponding solutions. Multiple control variables are introduced both in the objective function and constraints of the programming model, which make it possible for the constraints being relaxed under respective levels. A more satisfactory objective value can thus be expected as well as the impact of each constraint on the modeling outputs can be clarified effectively. The decision variables are useful for decision makers to justify and/or adjust the decision schemes for agricultural activities through incorporation of their implicit knowledge on water allocation management.     

A polyhedral approach to the alldifferent system

This paper examines the facial structure of the convex hull of integer vectors satisfying a system of alldifferent predicates, also called an alldifferent system. The underlying analysis is based on a property, called inclusion, pertinent to such a system. For the alldifferent systems for which this property holds, we present two families of facet-defining inequalities, establish that they completely describe the convex hull and show that they can be separated in polynomial time. Consequently, the inclusion property characterises a group of alldifferent systems for which the linear optimization problem (i.e. the problem of optimizing a linear function over that system) can be solved in polynomial time. Furthermore, we establish that, for systems with three predicates, the inclusion property is also a necessary condition for the convex hull to be described by those two families of inequalities. For the alldifferent systems that do not possess that property, we establish another family of facet-defining inequalities and an accompanied polynomial-time separation algorithm. All the separation algorithms are incorporated within a cutting-plane scheme and computational experience on a set of randomly generated instances is reported. In concluding, we show that the pertinence of the inclusion property can be decided in polynomial time.     

A viability approach to the skorohod problem

The theory of stochastic differential equations with reflecting boundary conditions leads to the "Skorohod" problem. Thispaper proposes a solution to this problem using techniques from viability theory and non-smooth analysis, allowing very general situations to occur.     

A random approach to the Lebesgue integral

We construct an integral of a measurable real function using randomly chosen Riemann sums and show that it converges in probability to the Lebesgue integral where this exists. We then prove some conditions for the almost sure convergence of this integral.     

A fuzzy approach to the transportation problem

The transportation problem with fuzzy supply values of the deliverers and with fuzzy demand values of the receivers is analysed. For the solution of the problem the technique of parametric programming is used. This makes it possible to obtain not only the maximizing solution (according to the Bellman-Zadeh criterion) but also other alternatives close to the optimal solution.     

A categorical approach to the maximum theorem

Berge's maximum theorem gives conditions ensuring the continuity of an optimised function as a parameter changes. In this paper we state and prove the maximum theorem in terms of the theory of monoidal topology and the theory of double categories.This approach allows us to generalise (the main assertion of) the maximum theorem, which is classically stated for topological spaces, to pseudotopological spaces and pretopological spaces, as well as to closure spaces, approach spaces and probabilistic approach spaces, amongst others. As a part of this we prove a generalisation of the extreme value theorem.