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Doctoral Thesis
DOI
https://doi.org/10.11606/T.3.2006.tde-15092006-155659
Document
Author
Full name
André Cury Maiali
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2006
Supervisor
Committee
Costa, Oswaldo Luiz do Valle (President)
Cipparrone, Flavio Almeida de Magalhaes
Pinto, Afonso de Campos
Piqueira, Jose Roberto Castilho
Rosenfeld, Rogério
Title in Portuguese
Controle ótimo estocástico a tempo discreto e espaço de estado contínuo aplicado a derivativos.
Keywords in Portuguese
Controle ótimo
Derivativos
Processos estocásticos
Abstract in Portuguese
Nesta tese abordamos o problema do hedging de mínima variância de derivativos em mercados incompletos usando a teoria de controle ótimo estocástico com critério quadrático de otimização. Desenvolvemos um modelo geral de apreçamento e hedging de derivativos em mercados incompletos, a tempo discreto, que é capaz de acomodar qualquer tipo de payoff com característica européia que dependa de n ativos de risco. Nesse modelo, o mercado pode apresentar diferentes modos de operação, o que foi formalizado matematicamente por meio de uma cadeia de Markov. Também desenvolvemos um modelo geral de apreçamento e hedging de derivativos em mercados incompletos, a tempo discreto e espaço de estados contínuo, que é capaz de acomodar qualquer tipo de payoff com característica européia que dependa de um ativo de risco cujos retornos sejam representados por um processo de difusão com saltos. Desenvolvemos, ainda, expressões analíticas fechadas para o apreçamento e hedging de uma opção de compra européia vanilla em duas situações: (1) quando os retornos do ativo de risco são representados por um processo de difusão com saltos, e (2) quando os retornos do ativo de risco são representados por um processo de Wiener. Por fim, realizamos simulações numéricas para o controle (hedging) de uma opção de compra européia vanilla quando os retornos do ativo de risco são representados por um processo de Wiener, e comparamos os resultados obtidos com a estratégia de controle derivada do modelo de Black & Scholes.
Title in English
Discrete-time, continuous state-space ctochastic optimal control applied to derivatives.
Keywords in English
Derivatives
Optimal control
Stochastic processes
Abstract in English
In this thesis we approach the mean-variance hedging problem of derivatives in incomplete markets employing the theory of stochastic optimal control with quadratic optimization criteria. We developed a general derivatives pricing and hedging model in incomplete markets, in discrete time, capable of accommodating any type of European payoff contingent on n risky assets. In this model, the market may exhibit different operating modes, which were mathematically formalized by means of a Markov chain. We also developed a general derivatives pricing and hedging model in incomplete markets, in discrete time and continuous state space, capable of accommodating any type of European payoff contingent on one risky asset whose returns are described by a jump diffusion process. Even further, we developed closed-form analytical expressions for the pricing and hedging of a European vanilla call option in two situations: (1) when the risky asset returns are described by a jump diffusion process, and (2) when the risky asset returns are described by a Wiener process. Finally, we simulated the control (hedging) of a European vanilla call option when the risky asset returns are described by a Wiener process, and compared the results to those obtained with the control strategy derived from the Black & Scholes model.
 
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Publishing Date
2006-11-16
 
WARNING: The material described below relates to works resulting from this thesis or dissertation. The contents of these works are the author's responsibility.
  • COSTA, O. L. V., MAIALI, A. C., and PINTO, Afonso de Campos. Sampled Control for Mean-Variance Hedging in a Jump Diffusion Financial Market [doi:10.1109/TAC.2010.2046923]. IEEE Transactions on Automatic Control [online], 2010, vol. 55, p. 1704-1709.
  • COSTA, O. L. V., MAIALI, A. C., and PINTO, Afonso de Campos. Sampled Control for Mean-Variance Hedging in a Jump Diffusion Financial Market. In 48th IEEE Conference on Decision and Control, Shanghai, 2009. The Combined 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference., 2009.
  • COSTA, O. L. V., MAIALI, André Cury, and PINTO, Afonso de Campos. Mean-Variance Hedging Strategies in Discrete Time and Continuous State Space. In COMPUTATIONAL FINANCE 2006, Londres, 2006. Computational Finance and its Applications II.Southampton, UK : WIT Press, 2006.
All rights of the thesis/dissertation are from the authors
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