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Tamer Basar - One of the best experts on this subject based on the ideXlab platform.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
Siam Journal on Control and Optimization, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear and the primitive random variables are Gaussian. Each of the two players/controllers of the system acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving...
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common Information based markov perfect equilibria for stochastic games with Asymmetric Information finite games
IEEE Transactions on Automatic Control, 2014Co-Authors: Ashutosh Nayyar, Abhishek Gupta, Cedric Langbort, Tamer BasarAbstract:A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different Information about the state and action processes is considered. The asymmetry of Information among the controllers makes it difficult to compute or characterize Nash equilibria. Using the common Information among the controllers, the game with Asymmetric Information is used to construct another game with symmetric Information such that the equilibria of the new game can be transformed to equilibria of the original game. Further, under certain conditions, a Markov state is identified for the new symmetric Information game and its Markov perfect equilibria are characterized. This characterization provides a backward induction algorithm to find Nash equilibria of the original game with Asymmetric Information in pure or behavioral strategies. Each step of this algorithm involves finding Bayesian Nash equilibria of a one-stage Bayesian game. The class of Nash equilibria of the original game that can be characterized in this backward manner are named common Information based Markov perfect equilibria.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
arXiv: Systems and Control, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving a sequence of linear equations. We also show through an example that there could be other Nash equilibria in a game of Asymmetric Information, not corresponding to common Information based Markov perfect equilibria.
Ashutosh Nayyar - One of the best experts on this subject based on the ideXlab platform.
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zero sum stochastic games with Asymmetric Information
arXiv e-prints, 2019Co-Authors: Dhruva Kartik, Ashutosh NayyarAbstract:A general model for zero-sum stochastic games with Asymmetric Information is considered. In this model, each player's Information at each time can be divided into a common Information part and a private Information part. Under certain conditions on the evolution of the common and private Information, a dynamic programming characterization of the value of the game (if it exists) is presented. If the value of the zero-sum game does not exist, then the dynamic program provides bounds on the upper and lower values of the game. This dynamic program is then used for a class of zero-sum stochastic games with complete Information on one side and partial Information on the other, that is, games where one player has complete Information about state, actions and observation history while the other player may only have partial Information about the state and action history. For such games, it is shown that the value exists and can be characterized using the dynamic program. It is further shown that for this class of games, the dynamic program can be used to compute an equilibrium strategy for the more informed player in which the player selects its action using its private Information and the common Information belief.
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zero sum stochastic games with Asymmetric Information
Conference on Decision and Control, 2019Co-Authors: Dhruva Kartik, Ashutosh NayyarAbstract:A general model for zero-sum stochastic games with Asymmetric Information is considered. For this model, a dynamic programming characterization of the value is presented under some assumptions on its existence. This dynamic program is then used for a class of zero-sum stochastic games with complete Information on one side and partial Information on the other, that is, games where one player has complete Information about state, actions and observation history while the other player may only have partial Information about the state and action history. For such games, the value is characterized using dynamic programming without making any existence assumptions. It is further shown that for this class of games, there exists a Nash equilibrium where the more informed player plays a common Information belief based strategy. A dynamic programming approach is presented for computing this strategy.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
Siam Journal on Control and Optimization, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear and the primitive random variables are Gaussian. Each of the two players/controllers of the system acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving...
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common Information based markov perfect equilibria for stochastic games with Asymmetric Information finite games
IEEE Transactions on Automatic Control, 2014Co-Authors: Ashutosh Nayyar, Abhishek Gupta, Cedric Langbort, Tamer BasarAbstract:A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different Information about the state and action processes is considered. The asymmetry of Information among the controllers makes it difficult to compute or characterize Nash equilibria. Using the common Information among the controllers, the game with Asymmetric Information is used to construct another game with symmetric Information such that the equilibria of the new game can be transformed to equilibria of the original game. Further, under certain conditions, a Markov state is identified for the new symmetric Information game and its Markov perfect equilibria are characterized. This characterization provides a backward induction algorithm to find Nash equilibria of the original game with Asymmetric Information in pure or behavioral strategies. Each step of this algorithm involves finding Bayesian Nash equilibria of a one-stage Bayesian game. The class of Nash equilibria of the original game that can be characterized in this backward manner are named common Information based Markov perfect equilibria.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
arXiv: Systems and Control, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving a sequence of linear equations. We also show through an example that there could be other Nash equilibria in a game of Asymmetric Information, not corresponding to common Information based Markov perfect equilibria.
Abhishek Gupta - One of the best experts on this subject based on the ideXlab platform.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
Siam Journal on Control and Optimization, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear and the primitive random variables are Gaussian. Each of the two players/controllers of the system acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving...
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common Information based markov perfect equilibria for stochastic games with Asymmetric Information finite games
IEEE Transactions on Automatic Control, 2014Co-Authors: Ashutosh Nayyar, Abhishek Gupta, Cedric Langbort, Tamer BasarAbstract:A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different Information about the state and action processes is considered. The asymmetry of Information among the controllers makes it difficult to compute or characterize Nash equilibria. Using the common Information among the controllers, the game with Asymmetric Information is used to construct another game with symmetric Information such that the equilibria of the new game can be transformed to equilibria of the original game. Further, under certain conditions, a Markov state is identified for the new symmetric Information game and its Markov perfect equilibria are characterized. This characterization provides a backward induction algorithm to find Nash equilibria of the original game with Asymmetric Information in pure or behavioral strategies. Each step of this algorithm involves finding Bayesian Nash equilibria of a one-stage Bayesian game. The class of Nash equilibria of the original game that can be characterized in this backward manner are named common Information based Markov perfect equilibria.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
arXiv: Systems and Control, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving a sequence of linear equations. We also show through an example that there could be other Nash equilibria in a game of Asymmetric Information, not corresponding to common Information based Markov perfect equilibria.
Cedric Langbort - One of the best experts on this subject based on the ideXlab platform.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
Siam Journal on Control and Optimization, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear and the primitive random variables are Gaussian. Each of the two players/controllers of the system acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving...
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common Information based markov perfect equilibria for stochastic games with Asymmetric Information finite games
IEEE Transactions on Automatic Control, 2014Co-Authors: Ashutosh Nayyar, Abhishek Gupta, Cedric Langbort, Tamer BasarAbstract:A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different Information about the state and action processes is considered. The asymmetry of Information among the controllers makes it difficult to compute or characterize Nash equilibria. Using the common Information among the controllers, the game with Asymmetric Information is used to construct another game with symmetric Information such that the equilibria of the new game can be transformed to equilibria of the original game. Further, under certain conditions, a Markov state is identified for the new symmetric Information game and its Markov perfect equilibria are characterized. This characterization provides a backward induction algorithm to find Nash equilibria of the original game with Asymmetric Information in pure or behavioral strategies. Each step of this algorithm involves finding Bayesian Nash equilibria of a one-stage Bayesian game. The class of Nash equilibria of the original game that can be characterized in this backward manner are named common Information based Markov perfect equilibria.
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common Information based markov perfect equilibria for linear gaussian games with Asymmetric Information
arXiv: Systems and Control, 2014Co-Authors: Abhishek Gupta, Ashutosh Nayyar, Cedric Langbort, Tamer BasarAbstract:We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic Information about the state process and the other controller's past actions and observations. This leads to a dynamic game of Asymmetric Information among the controllers. Building on our earlier work on finite games with Asymmetric Information, we devise an algorithm to compute a Nash equilibrium by using the common Information among the controllers. We call such equilibria common Information based Markov perfect equilibria of the game, which can be viewed as a refinement of Nash equilibrium in games with Asymmetric Information. If the players' cost functions are quadratic, then we show that under certain conditions a unique common Information based Markov perfect equilibrium exists. Furthermore, this equilibrium can be computed by solving a sequence of linear equations. We also show through an example that there could be other Nash equilibria in a game of Asymmetric Information, not corresponding to common Information based Markov perfect equilibria.
Victoria Ivashina - One of the best experts on this subject based on the ideXlab platform.
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Asymmetric Information effects on loan spreads
Journal of Financial Economics, 2009Co-Authors: Victoria IvashinaAbstract:Abstract This paper estimates the cost arising from Information asymmetry between the lead bank and members of the lending syndicate. In a lending syndicate, the lead bank retains only a fraction of the loan but acts as the intermediary between the borrower and the syndicate participants. Theory predicts that Asymmetric Information will cause participants to demand a higher interest rate and that a large loan ownership by the lead bank should reduce this effect. In equilibrium, however, the Asymmetric Information premium demanded by participants is offset by the diversification premium demanded by the lead. Using shifts in the idiosyncratic credit risk of the lead bank's loan portfolio as an instrument, I measure the Asymmetric Information effect of the lead's share on the loan spread and find that it accounts for approximately 4% of the total cost of credit.
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Asymmetric Information effects on loan spreads
Social Science Research Network, 2005Co-Authors: Victoria IvashinaAbstract:This paper estimates the cost arising from Information asymmetry between the lead bank and members of the lending syndicate. In a lending syndicate, the lead bank retains only a fraction of the loan but acts as the intermediary between the borrower and the syndicate participants. Theory predicts that private Information in the hands of the lead bank will cause syndicate participants to demand a higher interest rate and that a large loan ownership by the lead bank should reduce Asymmetric Information and the related premium. Nevertheless, the estimated OLS relation between the loan spread and the lead bank's share is positive. This result, however, ignores the fact that we only observe equilibrium outcomes and, therefore, the Asymmetric Information premium demanded by participants is offset by the diversification premium demanded by the lead bank. Using exogenous shifts in the credit risk of the lead bank's loan portfolio as an instrument, I measure the Asymmetric Information effect of the lead's share on the loan spread and find that it has a large economic cost, accounting for approximately 4 percent of the total cost of credit.
