A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises.
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/3/3139/tde-01072021-111725/ |
Resumo: | In this work, we study the stochastic multi-period optimal control for discrete-time linear systems subject to multiplicative noises. Initially, we consider a multi-period mean-variance trade-off performance criterion for the finite-horizon case with and without constraints, and then, its infinite-horizon case with the long-run as well as the discount factor criteria. We adopt the mean-field approach to tackle the problems and get their solutions in terms of a set of two generalised coupled algebraic Riccati equations (GCARE for short). For the finite-horizon case, we derive the optimal control law for a general multi-period mean-variance problem and obtain the optimal control strategy for the constrained problems using the Lagrangian multipliers approach. From the general unrestricted result, we obtain a sufficient condition for a closed-form solution for one of the constrained problems considered in this work. For the infinite-horizon case, we establish sufficient conditions for the existence of the maximal solution, necessary and sufficient conditions for the existence of the mean-square stabilising solution to the GCARE, and derive the optimal control laws for the discounted and long-run problems. When particularised to the portfolio selection problem, we show that our results match some of the results available in the literature. A numerical example illustrates the obtained optimal controls for the multi-period portfolio selection problem in which is desired to optimise the sum of the mean-variance trade-off costs of a portfolio against a benchmark along the time. |
id |
USP_93604c935e0e4325611a8cce003826b0 |
---|---|
oai_identifier_str |
oai:teses.usp.br:tde-01072021-111725 |
network_acronym_str |
USP |
network_name_str |
Biblioteca Digital de Teses e Dissertações da USP |
repository_id_str |
2721 |
spelling |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises.Uma abordagem de campos de médias para o controle ótimo de sistemas lineares em tempo discreto com ruídos multiplicativos.Controle estocásticoControle ótimoIntertemporal restrictionsLinear systemsOptimal controlOtimização de carteira de investimentosPortfolio optimisationRestrições intertemporaisSistemas linearesSolução estabilizadoraStabilising solutionStochastic controlIn this work, we study the stochastic multi-period optimal control for discrete-time linear systems subject to multiplicative noises. Initially, we consider a multi-period mean-variance trade-off performance criterion for the finite-horizon case with and without constraints, and then, its infinite-horizon case with the long-run as well as the discount factor criteria. We adopt the mean-field approach to tackle the problems and get their solutions in terms of a set of two generalised coupled algebraic Riccati equations (GCARE for short). For the finite-horizon case, we derive the optimal control law for a general multi-period mean-variance problem and obtain the optimal control strategy for the constrained problems using the Lagrangian multipliers approach. From the general unrestricted result, we obtain a sufficient condition for a closed-form solution for one of the constrained problems considered in this work. For the infinite-horizon case, we establish sufficient conditions for the existence of the maximal solution, necessary and sufficient conditions for the existence of the mean-square stabilising solution to the GCARE, and derive the optimal control laws for the discounted and long-run problems. When particularised to the portfolio selection problem, we show that our results match some of the results available in the literature. A numerical example illustrates the obtained optimal controls for the multi-period portfolio selection problem in which is desired to optimise the sum of the mean-variance trade-off costs of a portfolio against a benchmark along the time.Neste trabalho, estudamos o controle ótimo estocástico multi-período de sistemas lineares em tempo discreto sujeitos a ruidos multiplicativos. Inicialmente, consideramos como critério de desempenho a combinação multi-período entre média e variância para o caso de horizonte finito com e sem restrições, e posteriormente consideramos o caso de horizonte infinito com a abordagem de campos de médias para resolvermos os problemas e obtemos suas soluções em termos de um conjunto de duas equações generalizadas de Riccati (GCARE). Para o caso de horizonte finito, derivamos o controle ótimo para um problema geral de média variância multi-período e obtemos as estratégias de controle ótimo para os problemas com restrições através de multiplicadores de Lagrange. Do resultado geral sem restrições, obtemos condições suficientes para uma solução fechada para um dos problemas com restrições considerado neste trabalho. Para o caso de horizonte infinito, são fornecidas condições suficientes para a existência da solução máxima, condições necessárias e suficientes para a existência da solução estabilizadora de média quadrática da GCARE e derivamos as leis de controle ótimo para os problemas com critério de longo prazo e com fator de desconto. Quando particularizado para o problema de alocação de carteiras de investimento, mostramos que nossos resultados são equivalentes há alguns resultados disponíveis na literatura. Concluímos esta tese ilustrando os resultados obtidos com um problema multi-período de alocação de carteira de investimentos no qual é desejado otimizar a soma de médias e variâncias do valor da carteira versus um ativo de referência.Biblioteca Digitais de Teses e Dissertações da USPCosta, Oswaldo Luiz do ValleBarbieri, Fabio2020-10-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/3/3139/tde-01072021-111725/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2021-07-01T17:36:02Zoai:teses.usp.br:tde-01072021-111725Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212021-07-01T17:36:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. Uma abordagem de campos de médias para o controle ótimo de sistemas lineares em tempo discreto com ruídos multiplicativos. |
title |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
spellingShingle |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. Barbieri, Fabio Controle estocástico Controle ótimo Intertemporal restrictions Linear systems Optimal control Otimização de carteira de investimentos Portfolio optimisation Restrições intertemporais Sistemas lineares Solução estabilizadora Stabilising solution Stochastic control |
title_short |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
title_full |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
title_fullStr |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
title_full_unstemmed |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
title_sort |
A mean-field approach for the optimal control of discrete-time linear systems with multiplicative noises. |
author |
Barbieri, Fabio |
author_facet |
Barbieri, Fabio |
author_role |
author |
dc.contributor.none.fl_str_mv |
Costa, Oswaldo Luiz do Valle |
dc.contributor.author.fl_str_mv |
Barbieri, Fabio |
dc.subject.por.fl_str_mv |
Controle estocástico Controle ótimo Intertemporal restrictions Linear systems Optimal control Otimização de carteira de investimentos Portfolio optimisation Restrições intertemporais Sistemas lineares Solução estabilizadora Stabilising solution Stochastic control |
topic |
Controle estocástico Controle ótimo Intertemporal restrictions Linear systems Optimal control Otimização de carteira de investimentos Portfolio optimisation Restrições intertemporais Sistemas lineares Solução estabilizadora Stabilising solution Stochastic control |
description |
In this work, we study the stochastic multi-period optimal control for discrete-time linear systems subject to multiplicative noises. Initially, we consider a multi-period mean-variance trade-off performance criterion for the finite-horizon case with and without constraints, and then, its infinite-horizon case with the long-run as well as the discount factor criteria. We adopt the mean-field approach to tackle the problems and get their solutions in terms of a set of two generalised coupled algebraic Riccati equations (GCARE for short). For the finite-horizon case, we derive the optimal control law for a general multi-period mean-variance problem and obtain the optimal control strategy for the constrained problems using the Lagrangian multipliers approach. From the general unrestricted result, we obtain a sufficient condition for a closed-form solution for one of the constrained problems considered in this work. For the infinite-horizon case, we establish sufficient conditions for the existence of the maximal solution, necessary and sufficient conditions for the existence of the mean-square stabilising solution to the GCARE, and derive the optimal control laws for the discounted and long-run problems. When particularised to the portfolio selection problem, we show that our results match some of the results available in the literature. A numerical example illustrates the obtained optimal controls for the multi-period portfolio selection problem in which is desired to optimise the sum of the mean-variance trade-off costs of a portfolio against a benchmark along the time. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-10-16 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/3/3139/tde-01072021-111725/ |
url |
https://www.teses.usp.br/teses/disponiveis/3/3139/tde-01072021-111725/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
_version_ |
1809090277982339072 |