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Decentralized Interaction and Co-adaptation in the Repeated Prisoner's Dilemma

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  • Tomas Klos

Abstract

The purpose of this paper is to propose a nonparametric interest rate term structure model and investigate its implications on term structure dynamics and prices of interest rate derivative securities. The nonparametric spot interest rate process is estimated from the observed short-term interest rates following a robust estimation procedure and the market price of interest rate risk is estimated as implied from the historical term structure data. That is, instead of imposing a priori restrictions on the model, data are allowed to speak for themselves, and at the same time the model retains a parsimonious structure and the computational tractability. The model is implemented using historical Canadian interest rate term structure data. The parametric models with closed form solutions for bond and bond option prices, namely the Vasicek (1977) and CIR (1985) models, are also estimated for comparison purpose. The empirical results not only provide strong evidence that the traditional spot interest rate models and market prices of interest rate risk are severely misspecified but also suggest that different model specifications have significant impact on term structure dynamics and prices of interest rate derivative securities.
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  • Tomas Klos, "undated". "Decentralized Interaction and Co-adaptation in the Repeated Prisoner's Dilemma," Computing in Economics and Finance 1997 88, Society for Computational Economics.
  • Handle: RePEc:sce:scecf7:88
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    1. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
    2. Nelson Minar & Rogert Burkhart & Chris Langton & Manor Askenazi, 1996. "The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations," Working Papers 96-06-042, Santa Fe Institute.
    3. Ho, Teck-Hua, 1996. "Finite automata play repeated prisoner's dilemma with information processing costs," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 173-207.
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    5. Stanley, E. Ann & Ashlock, Dan & Tesfatsion, Leigh, 1993. "Iterated Prisoner's Dilemma with Choice and Refusal of Partners," ISU General Staff Papers 199302010800001028, Iowa State University, Department of Economics.
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    7. Binmore, Kenneth G. & Samuelson, Larry, 1992. "Evolutionary stability in repeated games played by finite automata," Journal of Economic Theory, Elsevier, vol. 57(2), pages 278-305, August.
    8. Robert Hoffmann & Nigel Waring, 1996. "The Localisation of Interaction and Learning in the Repeated Prisoner's Dilemma," Working Papers 96-08-064, Santa Fe Institute.
    9. Kirchkamp, Oliver, 2000. "Spatial evolution of automata in the prisoners' dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 239-262, October.
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    Cited by:

    1. Klos, Tomas B. & Nooteboom, Bart, 1997. "Adaptive governance: the role of loyalty," Research Report 97B53, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Rudolf Vetschera, 2003. "Experimentation and Learning in Repeated Cooperation," Computational and Mathematical Organization Theory, Springer, vol. 9(1), pages 37-60, May.
    3. Klos, Tomas B. & Nooteboom, Bart, 2001. "Agent-based computational transaction cost economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 503-526, March.
    4. Giampiero E.G. Beroggi, 2000. "Dynamic Plots in Virtual Negotiations," Computational and Mathematical Organization Theory, Springer, vol. 6(2), pages 171-190, July.
    5. Tomas Klos, 1999. "Governance and Matching," Computing in Economics and Finance 1999 341, Society for Computational Economics.
    6. Peter Revay & Claudio Cioffi-Revilla, 2018. "Survey of evolutionary computation methods in social agent-based modeling studies," Journal of Computational Social Science, Springer, vol. 1(1), pages 115-146, January.

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