Search results for " optimization."
showing 10 items of 2333 documents
Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach
2019
Abstract This paper develops a novel approach to assess liquidity-adjusted Value-at-Risk (LVaR) optimization of multi-asset portfolios based on vine copulas and LVaR models. This framework is applied to stock markets of the G-7 countries, gold, commodities and Bitcoin. The results show that our approach is superior to the classical mean–variance Markowitz portfolio technique in terms of the optimal portfolio selection under a number of realistic operational and budget constraints. We find that both Bitcoin and gold improves the risk-return performance of the G-7 stock portfolio. However, Bitcoin (gold) performs better under a scenario of only long-positions (when short-selling is allowed).
A multi-local optimization algorithm
1998
The development of efficient algorithms that provide all the local minima of a function is crucial to solve certain subproblems in many optimization methods. A “multi-local” optimization procedure using inexact line searches is presented, and numerical experiments are also reported. An application of the method to a semi-infinite programming procedure is included.
The rank of random regular digraphs of constant degree
2018
Abstract Let d be a (large) integer. Given n ≥ 2 d , let A n be the adjacency matrix of a random directed d -regular graph on n vertices, with the uniform distribution. We show that the rank of A n is at least n − 1 with probability going to one as n grows to infinity. The proof combines the well known method of simple switchings and a recent result of the authors on delocalization of eigenvectors of A n .
The Serial Property and Restricted Balanced Contributions in discrete cost sharing problems
2006
We show that the Serial Poperty and Restricted Balanced Contributions characterize the subsidy-free serial cost sharing method (Moulin (1995)) in discrete cost allocation problems.
Hores: A timetabling system for Spanish secondary schools
1995
Constructing a timetable is a difficult problem faced by every school every year. A feasible solution has to satisfy many different requirements and constraints. A good solution has to provide compact timetables for classes and teachers. In order to help the schools, we have developed HORES, a robust and flexible timetabling system suited to the needs of Spanish secondary schools. HORES runs on a PC and is fast and user-friendly. It may handle virtually every condition required by the schools and obtains good quality solutions in very short computing times. It also allows the user to modify interactively the solutions. HORES is now being used by schools with satisfactory results.
Stochastic Learning for SAT- Encoded Graph Coloring Problems
2010
The graph coloring problem (GCP) is a widely studied combinatorial optimization problem due to its numerous applications in many areas, including time tabling, frequency assignment, and register allocation. The need for more efficient algorithms has led to the development of several GC solvers. In this paper, the authors introduce a team of Finite Learning Automata, combined with the random walk algorithm, using Boolean satisfiability encoding for the GCP. The authors present an experimental analysis of the new algorithm’s performance compared to the random walk technique, using a benchmark set containing SAT-encoding graph coloring test sets.
Analyzing Temperature Effects on Mortality Within theREnvironment: The Constrained Segmented Distributed Lag Parameterization
2010
Here we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.
Weighted samples, kernel density estimators and convergence
2003
This note extends the standard kernel density estimator to the case of weighted samples in several ways. In the first place I consider the obvious extension by substituting the simple sum in the definition of the estimator by a weighted sum, but I also consider other alternatives of introducing weights, based on adaptive kernel density estimators, and consider the weights as indicators of the informational content of the observations and in this sense as signals of the local density of the data. All these ideas are shown using the Penn World Table in the context of the macroeconomic convergence issue.
Balanced Asymmetrical Nearly Orthogonal Designs for first and second order effect estimation
2006
Abstract A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interaction estimability requirements with a number of runs as small as possible, is proposed in this paper. The method, based on a heuristic procedure, uses a new optimality criterion formulated here. The proposed method demonstrates efficiency in terms of searching time and optimality of the attained designs. A complete collection of such asymmetrical designs with two- and three-level factors is available. A technological application is also presented.
Establishing some order amongst exact approximations of MCMCs
2016
Exact approximations of Markov chain Monte Carlo (MCMC) algorithms are a general emerging class of sampling algorithms. One of the main ideas behind exact approximations consists of replacing intractable quantities required to run standard MCMC algorithms, such as the target probability density in a Metropolis-Hastings algorithm, with estimators. Perhaps surprisingly, such approximations lead to powerful algorithms which are exact in the sense that they are guaranteed to have correct limiting distributions. In this paper we discover a general framework which allows one to compare, or order, performance measures of two implementations of such algorithms. In particular, we establish an order …