The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Brian D. O. Anderson - One of the best experts on this subject based on the ideXlab platform.
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A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2011Co-Authors: Yantao Feng, Brian D. O. Anderson, Andras Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
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An iterative algorithm to solve state-perturbed stochastic algebraic Riccati equations in LQ zero-sum games
Systems & Control Letters, 2009Co-Authors: Yantao Feng, Brian D. O. AndersonAbstract:An iterative algorithm to solve a kind of state-perturbed stochastic algebraic Riccati equation (SARE) in LQ zero-sum game problems is proposed. In our algorithm, we replace the problem of solving a SARE with an indefinite Quadratic Term by the problem of solving a sequence of SAREs with a negative semidefinite Quadratic Term, which can be solved by existing methods. Under some appropriate conditions, we prove that our algorithm is globally convergent. We give a numerical example to show the effectiveness of our algorithm. Our algorithm also has a natural game theoretic interpretation.
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On an iterative algorithm to compute the positive stabilizing solution of generalized algebraic Riccati equations
2009 Chinese Control and Decision Conference, 2009Co-Authors: Yantao Feng, Brian D. O. AndersonAbstract:An iterative algorithm to solve a kind of generalized algebraic Riccati equations (GARE) in LQ stochastic zero-sum game problems is proposed. In our algorithm, we replace the problem of solving a GARE with an indefinite Quadratic Term by the problem of solving a sequence of GARE with a negative semidefinite Quadratic Term which can be solved by existing methods. Under some appropriate conditions, we prove that our algorithm is globally convergent.
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CDC - A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2008Co-Authors: Yantao Feng, Brian D. O. Anderson, Andreas Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
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computing the positive stabilizing solution to algebraic riccati equations with an indefinite Quadratic Term via a recursive method
IEEE Transactions on Automatic Control, 2008Co-Authors: Alexander Lanzon, Yantao Feng, Brian D. O. Anderson, Michael RotkowitzAbstract:An iterative algorithm to solve algebraic riccati equations with an indefinite Quadratic Term is proposed. The global convergence and local Quadratic rate of convergence of the algorithm are guaranteed and a proof is given. Numerical examples are also provided to demonstrate the superior effectiveness of the proposed algorithm when compared with methods based on finding stable invariant subspaces of Hamiltonian matrices. A game theoretic interpretation of the algorithm is also provided.
Yantao Feng - One of the best experts on this subject based on the ideXlab platform.
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A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2011Co-Authors: Yantao Feng, Brian D. O. Anderson, Andras Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
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An iterative algorithm to solve state-perturbed stochastic algebraic Riccati equations in LQ zero-sum games
Systems & Control Letters, 2009Co-Authors: Yantao Feng, Brian D. O. AndersonAbstract:An iterative algorithm to solve a kind of state-perturbed stochastic algebraic Riccati equation (SARE) in LQ zero-sum game problems is proposed. In our algorithm, we replace the problem of solving a SARE with an indefinite Quadratic Term by the problem of solving a sequence of SAREs with a negative semidefinite Quadratic Term, which can be solved by existing methods. Under some appropriate conditions, we prove that our algorithm is globally convergent. We give a numerical example to show the effectiveness of our algorithm. Our algorithm also has a natural game theoretic interpretation.
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On an iterative algorithm to compute the positive stabilizing solution of generalized algebraic Riccati equations
2009 Chinese Control and Decision Conference, 2009Co-Authors: Yantao Feng, Brian D. O. AndersonAbstract:An iterative algorithm to solve a kind of generalized algebraic Riccati equations (GARE) in LQ stochastic zero-sum game problems is proposed. In our algorithm, we replace the problem of solving a GARE with an indefinite Quadratic Term by the problem of solving a sequence of GARE with a negative semidefinite Quadratic Term which can be solved by existing methods. Under some appropriate conditions, we prove that our algorithm is globally convergent.
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CDC - A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2008Co-Authors: Yantao Feng, Brian D. O. Anderson, Andreas Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
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computing the positive stabilizing solution to algebraic riccati equations with an indefinite Quadratic Term via a recursive method
IEEE Transactions on Automatic Control, 2008Co-Authors: Alexander Lanzon, Yantao Feng, Brian D. O. Anderson, Michael RotkowitzAbstract:An iterative algorithm to solve algebraic riccati equations with an indefinite Quadratic Term is proposed. The global convergence and local Quadratic rate of convergence of the algorithm are guaranteed and a proof is given. Numerical examples are also provided to demonstrate the superior effectiveness of the proposed algorithm when compared with methods based on finding stable invariant subspaces of Hamiltonian matrices. A game theoretic interpretation of the algorithm is also provided.
Marco Lovera - One of the best experts on this subject based on the ideXlab platform.
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A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2011Co-Authors: Yantao Feng, Brian D. O. Anderson, Andras Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
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CDC - A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2008Co-Authors: Yantao Feng, Brian D. O. Anderson, Andreas Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
Andras Varga - One of the best experts on this subject based on the ideXlab platform.
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A New Iterative Algorithm to Solve Periodic Riccati Differential Equations With Sign Indefinite Quadratic Terms
IEEE Transactions on Automatic Control, 2011Co-Authors: Yantao Feng, Brian D. O. Anderson, Andras Varga, Marco LoveraAbstract:An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite Quadratic Term is proposed. In our algorithm, we replace the problem of solving a PRDE with an indefinite Quadratic Term by the problem of solving a sequence of PRDEs with a negative semidefinite Quadratic Term which can be solved by existing methods. The global convergence and the local Quadratic rate of convergence are both established. A numerical example is given to illustrate our algorithm.
Liuren Wu - One of the best experts on this subject based on the ideXlab platform.
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design and estimation of Quadratic Term structure models
Review of Finance, 2003Co-Authors: Markus Leippold, Liuren WuAbstract:We consider the design and estimation of Quadratic Term structure models. We start with a list of stylized facts on interest rates and interest rate derivatives, classified into three layers: (1) general statistical properties, (2) forecasting relations, and (3) conditional dynamics. We then investigate the implications of each layer of property on model design and strive to establish a mapping between evidence and model structures. We calibrate a two-factor model that approximates these three layers of properties well, and show that a flexible specification for the market price of risk is important in capturing the stylized evidence in forecasting relations while factor interactions are indispensable in generating the hump-shaped dynamics of bond yields. JEL classification codes: G12, G13, E43.
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design and estimation of Quadratic Term structure models
The Finance, 2002Co-Authors: Markus Leippold, Liuren WuAbstract:We consider the design and estimation of Quadratic Term structure models. We start with a list of stylized facts on interest rates and interest rate derivatives, classified into three layers: (1) general statistical properties, (2) forecasting relations, and (3) conditional dynamics. We then investigate the implications of each layer of property on model design and strive to establish a mapping between evidence and model structures. We calibrate a twofactor model that approximates these three layers of properties well, and illustrate how the model can be applied to pricing interest rate derivatives.
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Quadratic Term structure models
2000Co-Authors: Markus Leippold, Liuren WuAbstract:We identify and characterize a class of Term structure models where bond yields are Quadratic functions of the Markov process. We label this class as the 'Quadratic class' and aim to lay a solid theoretical foundation for its future empirical application. We contribute to the literature in three aspects: (i) We identify the necessary and sufficient conditions for the Quadratic class in Terms of the Markov process, the instantaneous interest rate, and the pricing kernel. (ii) We characterize the properties of the bond yields and forward rates in Terms of their moment conditions and characteristic functions. (iii) We provide closed-form solutions to a wide variety of fixed income derivatives.
