The Institutional Environment and the Banking - Growth Nexus: Theory and Investigation for MENA

This paper seeks to provide some theoretical and empirical answers to the following question: Does the institutional environment affect the causality relationship between banking development and economic growth? In the theoretical part, we develop an endogenous growth model where the institutional environment is captured through two indicators: the judicial system efficiency and the easiness of informal trade. We show that an improvement of the institutional environment has two effects. First, it intensifies the causality direction from banking to economic growth through a reduction of defaulting loans. Second, it reduces the interest rate spread. In the empirical part, considering twenty-two MENA countries over the period 1984-2004, we find a bi-directional causality. The first one, which runs from banking development to economic growth, is more intense in countries with a more developed institutional environment. The second causality runs from economic growth to banking and indicates that a more developed economy has a more developed banking system.Banking; Growth; Institutions; MENA

Integrating continuous differential evolution with discrete local search for meander line RFID antenna design

The automated design of meander line RFID antennas is a discrete self-avoiding walk(SAW) problem for which efficiency is to be maximized while resonant frequency is to beminimized. This work presents a novel exploration of how discrete local search may beincorporated into a continuous solver such as differential evolution (DE). A prior DE algorithmfor this problem that incorporates an adaptive solution encoding and a bias favoringantennas with low resonant frequency is extended by the addition of the backbite localsearch operator and a variety of schemes for reintroducing modified designs into the DEpopulation. The algorithm is extremely competitive with an existing ACO approach and thetechnique is transferable to other SAW problems and other continuous solvers. The findingsindicate that careful reintegration of discrete local search results into the continuous populationis necessary for effective performance

A comparative study of multi objective optimization algorithms for a cellular automata model

Cellular Automata (CA) models can represent dynamic systems which are discrete in space and time that reflects the effect of intrinsic parameters where individual events are considered to occur from randomness. A CA model of two agents' chemical kinetics has been optimized earlier using NSGA-II based on Evolutionary Algorithm (EA). But the stochastic nature of the CA model along with its high sensitivity on the model parameters requires extensive investigation using different optimization algorithms. For this purpose, in the current study, four more recently developed and popular optimization algorithms based on EA, called NSGA-IIr, NSGA-IIa, AbYSS and MOEA/D, have been considered for investigation based on various performance measuring parameters. The study also compares the performances of the algorithms for different computational efforts with an objective to minimize the required number of objective function evaluations. Simulation results and Friedman rank statistical test show NSGA-IIa and NSGA-IIr as the best choices to optimize the CA stochastic model across any number of objective function evaluations. Though the choice of optimization algorithm does not change with function evaluations, higher function evaluations improve the pseudo-pareto front for the CA optimization problem. Such results will facilitate the use of stochastic CA models to represent complex (bio)-chemical networks

Multifractality of Deutschemark/US Dollar Exchange Rates

This paper presents the first empirical investigation of the Multifractal Model of Asset Returns ("MMAR"). The MMAR, developed in Mandelbrot, Fisher, and Calvet (1997), is an alternative to ARCH-type representations for modelling temporal heterogeneity in financial returns. Typically, researchers introduce temporal heterogeneity through time-varying conditional second moments in a discrete time framework. Multifractality introduces a new source of heterogeneity through time-varying local regularity in the price path. The concept of local Holder exponent describes local regularity. Multifractal processes bridge the gap between locally Gaussian (Ito) diffusions and jump-diffusions by allowing a multiplicity of Holder exponents. This paper investigates multifractality in Deutschemark/US Dollar currency exchange rates. After finding evidence of multifractal scaling, we show how to estimate the multifractal spectrum via the Legendre transform. The scaling laws found in the data are replicated in simulations. Further simulation experiments test whether alternative representations, such as FIGARCH, are likely to replicate the multifractal signature of the Deutschemark/US Dollar data. On the basis of this evidence, the MMAR hypothesis appears more likely. Overall, the MMAR is quite successful in uncovering a previously unseen empirical regularity. Additionally, the model generates realistic sample paths, and opens the door to new theoretical and applied approaches to asset pricing and risk valuation. We conclude by advocating further empirical study of multifractality in financial data, along with more intensive study of estimation techniques and inference procedures.Multifractal model of asset returns, multifractal process, compound stochastic process, trading time, time deformation, scaling laws, multiscaling, self-similarity, self-affinity

Analytical Determination of a Helicopter Height Velocity Diagram

A helicopter height velocity (HV) diagram was analytically constructed using optimal control techniques. A three degree of freedom, point-mass, dynamic model was developed and validated with flight test data. An induced velocity calculation was incorporated which addressed the effects of vortex ring state. The problem was posed as an open final time, constrained initial state, constrained final state problem, with the objective function as a weighted sum of the initial altitude and quadratic controls. This formulation was solved using direct pseudo-spectral collocation and adaptive mesh refinement as implemented by the GPOPS-II® software suite. Proper adjustment of path constraints was crucial in achieving solutions which were comparable with flight test data. Results compare favorably with flight test data and previous analytical HV diagrams