Search results for "optimization"

showing 10 items of 2824 documents

Portfolio optimisation with strictly positive transaction costs and impulse control

1998

One crucial assumption in modern portfolio theory of continuous-time models is the no transaction cost assumption. This assumption normally leads to trading strategies with infinite variation. However, following such a strategy in the presence of transaction costs will lead to immediate ruin. We present an impulse control approach where the investor can change his portfolio only finitely often in finite time intervals. Further, we consider transaction costs including a fixed and a proportional cost component. For the solution of the resulting control problems we present a formal optimal stopping approach and an approach using quasi-variational inequalities. As an application we derive a non…

Statistics and ProbabilityTransaction costMathematical optimizationExponential utilityMerton's portfolio problemReplicating portfolioEconomicsPortfolio optimisation transaction costs impulse control asymptotic analysis.PortfolioOptimal stoppingStatistics Probability and UncertaintyPortfolio optimizationFinanceModern portfolio theory
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Newton algorithm for Hamiltonian characterization in quantum control

2014

We propose a Newton algorithm to characterize the Hamiltonian of a quantum system interacting with a given laser field. The algorithm is based on the assumption that the evolution operator of the system is perfectly known at a fixed time. The computational scheme uses the Crank-Nicholson approximation to explicitly determine the derivatives of the propagator with respect to the Hamiltonians of the system. In order to globalize this algorithm, we use a continuation method that improves its convergence properties. This technique is applied to a two-level quantum system and to a molecular one with a double-well potential. The numerical tests show that accurate estimates of the unknown paramete…

Statistics and Probability[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC][ PHYS.QPHY ] Physics [physics]/Quantum Physics [quant-ph]Non uniquenessFOS: Physical sciencesGeneral Physics and AstronomyQuantum controlsymbols.namesake[PHYS.QPHY]Physics [physics]/Quantum Physics [quant-ph]Fixed time[ CHIM.OTHE ] Chemical Sciences/OtherQuantum systemNumerical testsMathematical PhysicsMathematicsQuantum PhysicsPropagatorStatistical and Nonlinear PhysicsNMRContinuation methodModeling and Simulationsymbolsinverse problemidentification02.30.Yy Control theory02.30.Tb Operator theory42.50.Ct Quantum description of interaction of light and matter; related experiments02.60.Cb Numerical simulation; solution of equations03.65.Ge Solutions of wave equations: bound states02.30.Mv Approximations and expansions[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Quantum Physics (quant-ph)Hamiltonian (quantum mechanics)[CHIM.OTHE]Chemical Sciences/OtherAlgorithmcontrol
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Approachability in Population Games

2014

This paper reframes approachability theory within the context of population games. Thus, whilst one player aims at driving her average payoff to a predefined set, her opponent is not malevolent but rather extracted randomly from a population of individuals with given distribution on actions. First, convergence conditions are revisited based on the common prior on the population distribution, and we define the notion of \emph{1st-moment approachability}. Second, we develop a model of two coupled partial differential equations (PDEs) in the spirit of mean-field game theory: one describing the best-response of every player given the population distribution (this is a \emph{Hamilton-Jacobi-Bell…

Statistics and Probabilityeducation.field_of_studyComputer Science::Computer Science and Game TheoryMEAN-FIELD GAMESComputer scienceApproachabilityREGRETApplied MathematicsPopulationStochastic gameRegretContext (language use)91A13ApproachabilityEVOLUTIONComplete informationOptimization and Control (math.OC)Modeling and SimulationBest responseFOS: MathematicseducationMathematical economicsGame theoryMathematics - Optimization and Controlpopulation games
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Extremal polynomials in stratified groups

2018

We introduce a family of extremal polynomials associated with the prolongation of a stratified nilpotent Lie algebra. These polynomials are related to a new algebraic characterization of abnormal subriemannian geodesics in stratified nilpotent Lie groups. They satisfy a set of remarkable structure relations that are used to integrate the adjoint equations.

Statistics and Probabilityextremal polynomialsMathematics - Differential GeometryPure mathematicsGeodesicStructure (category theory)Group Theory (math.GR)Characterization (mathematics)algebra01 natural sciencesdifferentiaaligeometriaMathematics - Analysis of PDEsMathematics - Metric Geometry53C17FOS: Mathematics0101 mathematicsAlgebraic numberMathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17; 49K30; 17B70Mathematics - Optimization and ControlMathematics010102 general mathematicsStatisticsta111polynomitProlongation53C17 49K30 17B70Lie groupMetric Geometry (math.MG)abnormal extremals010101 applied mathematicsNilpotent Lie algebraNilpotentsub-Riemannian geometryabnormal extremals extremal polynomials Carnot groups sub-Riemannian geometryAbnormal extremals; Carnot groups; Extremal polynomials; Sub-Riemannian geometry; Analysis; Statistics and Probability; Geometry and Topology; Statistics Probability and UncertaintyDifferential Geometry (math.DG)Optimization and Control (math.OC)Carnot groups17B70Probability and UncertaintyGeometry and TopologyStatistics Probability and UncertaintyMathematics - Group TheoryAnalysisAnalysis of PDEs (math.AP)Mathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17 49K30 17B7049K30
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Robust Mean Field Games

2015

Recently there has been renewed interest in large-scale games in several research disciplines, with diverse application domains as in the smart grid, cloud computing, financial markets, biochemical reaction networks, transportation science, and molecular biology. Prior works have provided rich mathematical foundations and equilibrium concepts but relatively little in terms of robustness in the presence of uncertainties. In this paper, we study mean field games with uncertainty in both states and payoffs. We consider a population of players with individual states driven by a standard Brownian motion and a disturbance term. The contribution is threefold: First, we establish a mean field syste…

Statistics and Probabilitygame theory0209 industrial biotechnologyEconomics and EconometricsMathematical optimizationPopulationCloud computing02 engineering and technology01 natural sciencessymbols.namesake020901 industrial engineering & automationResource (project management)Wiener processSettore ING-INF/04 - AutomaticaRobustness (computer science)0101 mathematicseducationMathematicseducation.field_of_studybusiness.industryApplied Mathematics010102 general mathematicsComputer Graphics and Computer-Aided DesignComputer Science ApplicationsTerm (time)Computational MathematicsSmart gridComputational Theory and MathematicsNash equilibriumsymbolsmean field gamestochastic optimal controlSettore MAT/09 - Ricerca OperativabusinessMathematical economics
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On Limiting Fréchet ε-Subdifferentials

1998

This paper presents an e-sub differential calculus for nonconvex and nonsmooth functions. We extend the previous work by Jofre et all to the case where the functions are lower semicontinuous instead of locally Lipschitz.

Statistics::Machine LearningPure mathematicsWork (thermodynamics)Tangent coneMathematics::Optimization and ControlDifferential calculusLimitingLipschitz continuityMathematics
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Robust linear quadratic mean-field games in crowd-seeking social networks.

2013

We consider a social network where opinions evolve following a stochastic averaging process under the influence of adversarial disturbances. We provide a robust mean-field game model in the spirit of H∞-optimal control, establish existence of a mean-field equilibrium, and analyze its stochastic stability.

Stochastic controlContinuous-time stochastic processMathematical optimizationSocial networkStochastic processbusiness.industryControl (management)mean field gamesRobust controlStochastic neural networkbusinessGame theoryMathematical economicsMathematics
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Stochastic acceleration in generalized squared Bessel processes

2015

We analyze the time behavior of generalized squared Bessel processes, which are useful for modeling the relevant scales of stochastic acceleration problems. These nonstationary stochastic processes obey a Langevin equation with a non-Gaussian multiplicative noise. We obtain the long-time asymptotic behavior of the probability density function for non-Gaussian white and colored noise sources. We find that the functional form of the probability density functions is independent of the statistics of the noise source considered. Theoretical results are in good agreement with those obtained by numerical simulations of the Langevin equation with pulse noise sources.

Stochastic controlGeneralized inverse Gaussian distributionStatistics and ProbabilityMathematical optimizationBessel processexact resultStatistical and Nonlinear Physicsstochastic processes (theory)Noise (electronics)Multiplicative noiseLangevin equationStochastic differential equationColors of noiseStatistical physicsstochastic particle dynamics (theory)Statistics Probability and UncertaintyMathematicsStatistical and Nonlinear Physic
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A Fokker–Planck control framework for multidimensional stochastic processes

2013

AbstractAn efficient framework for the optimal control of probability density functions (PDFs) of multidimensional stochastic processes is presented. This framework is based on the Fokker–Planck equation that governs the time evolution of the PDF of stochastic processes and on tracking objectives of terminal configuration of the desired PDF. The corresponding optimization problems are formulated as a sequence of open-loop optimality systems in a receding-horizon control strategy. Many theoretical results concerning the forward and the optimal control problem are provided. In particular, it is shown that under appropriate assumptions the open-loop bilinear control function is unique. The res…

Stochastic controlMathematical optimizationContinuous-time stochastic processOptimization problemoptimal control stochastic processesStochastic processApplied MathematicsOptimal controlComputational MathematicsModel predictive controlMultidimensional stochastic processOptimal control theoryLimit cycleProbability density functionFokker–Planck equationFokker–Planck equationModel predictive controlMathematicsJournal of Computational and Applied Mathematics
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European Option Pricing and Hedging with Both Fixed and Proportional Transaction Costs

2003

Abstract In this paper we provide a systematic treatment of the utility based option pricing and hedging approach in markets with both fixed and proportional transaction costs: we extend the framework developed by Davis et al. (SIAM J. Control Optim., 31 (1993) 470) and formulate the option pricing and hedging problem. We propose and implement a numerical procedure for computing option prices and corresponding optimal hedging strategies. We present a careful analysis of the optimal hedging strategy and elaborate on important differences between the exact hedging strategy and the asymptotic hedging strategy of Whalley and Wilmott (RISK 7 (1994) 82). We provide a simulation analysis in order …

Stochastic controlTransaction costEconomics and EconometricsMathematical optimizationControl and OptimizationApplied MathematicsMonte Carlo methods for option pricingjel:C61Implied volatilityjel:G13jel:G11option pricing transaction costs stochastic control Markov chain approximationMicroeconomicsVariable pricingOrder (business)Valuation of optionsEconomicsAsian optionFinite difference methods for option pricingSSRN Electronic Journal
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