Search results for " optimization."

When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators

2011

The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization. Here we empirically compare the performance of 9 improved covariance estimation procedures by using daily returns of 90 highly capitalized US stocks for the period 1997-2007. We find that the usefulness of covariance matrix estimators strongly depends on the ratio between estimation period T and number of stocks N, on the presence or absence of short selling, and on the performance metric considered. When short selling is allowed, several estimation methods achieve a realized risk that is significantly smaller than the one obtai…

Cluster analysis for portfolio optimization

2005

We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio composition of the selected portfolio for a given value of the portfolio return are also investigated for each considered filtering method.

Simultaneously recovering potentials and embedded obstacles for anisotropic fractional Schrödinger operators

2017

Let \begin{document}$A∈{\rm{Sym}}(n× n)$\end{document} be an elliptic 2-tensor. Consider the anisotropic fractional Schrodinger operator \begin{document}$\mathscr{L}_A^s+q$\end{document} , where \begin{document}$\mathscr{L}_A^s: = (-\nabla·(A(x)\nabla))^s$\end{document} , \begin{document}$s∈ (0, 1)$\end{document} and \begin{document}$q∈ L^∞$\end{document} . We are concerned with the simultaneous recovery of \begin{document}$q$\end{document} and possibly embedded soft or hard obstacles inside \begin{document}$q$\end{document} by the exterior Dirichlet-to-Neumann (DtN) map outside a bounded domain \begin{document}$Ω$\end{document} associated with \begin{document}$\mathscr{L}_A^s+q$\end{docume…

Nuclear magnetic resonance: The contrast imaging problem

2011

Starting as a tool for characterization of organic molecules, the use of NMR has spread to areas as diverse as pharmacology, medical diagnostics (medical resonance imaging) and structural biology. Recent advancements on the study of spin dynamics strongly suggest the efficiency of geometric control theory to analyze the optimal synthesis. This paper focuses on a new approach to the contrast imaging problem using tools from geometric optimal control. It concerns the study of an uncoupled two-spin system and the problem is to bring one spin to the origin of the Bloch ball while maximizing the modulus of the magnetization vector of the second spin. It can be stated as a Mayer-type optimal prob…

Indicators of Errors for Approximate Solutions of Differential Equations

2014

Error indicators play an important role in mesh-adaptive numerical algorithms, which currently dominate in mathematical and numerical modeling of various models in physics, chemistry, biology, economics, and other sciences. Their goal is to present a comparative measure of errors related to different parts of the computational domain, which could suggest a reasonable way of improving the finite dimensional space used to compute the approximate solution. An “ideal” error indicator must possess several properties: efficiency, computability, and universality. In other words, it must correctly reproduce the distribution of errors, be indeed computable, and be applicable to a wide set of approxi…

Special Section on Fractional Operators in the Analysis of Mechanical Systems Under Stochastic Agencies

2017

Improved Neural Networks with Random Weights for Short-Term Load Forecasting.

2015

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load…

Conductivity reconstructions using real data from a new planar electrical impedance tomography device

2013

Abstract In this paper, we present results of reconstructions using real data from a new planar electrical impedance tomography device developed at the Institut fur Physik, Johannes Gutenberg Universitat, Mainz, Germany. The prototype consists of a planar sensing head of circular geometry, and it was designed mainly for breast cancer detection. There are 12 large outer electrodes arranged on a ring of radius  cm where the external currents are injected, and a set of 54 point-like high-impedance inner electrodes where the induced voltages are measured. Two direct (i.e. non-iterative) reconstruction algorithms are considered: one is based on a discrete resistor model, and the other one is an …

Optimal β-beam at the CERN-SPS

2006

In this talk, based on the work [J. Burguet-Castell et al., Nucl. Phys. B 725 (2005) 306], we present an analysis of the sensitivity to the mixing angle θ 13 and the CP-violating phase δ that could be achieved by a β-beam experiment based at the SPS accelerator at CERN. We estimate the optimal γ boost of the 6He and 18Ne ions for the proposed baseline CERN-Frejus (130 km), and also perform a simultaneous optimization of the ion boost and the baseline. A possible improvement of the current SPS accelerator is considered as well. After comparing the sensitivities of all relevant setups, we conclude that a β-beam running at the maximum acceleration achievable by the SPS, γ = 150 / 250 , and wit…

High selective H-plane TE dual mode cavity filter design by using nonresonating nodes

2013

The design of H-plane TE dual mode cavity filters using models containing nonresonating nodes is presented. From the models a coupling matrix is derived and decomposed into submatrices, each representing a subcircuit. The optimization and cascading of subcircuits represents a good starting point for the global optimization. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:161–166, 2014