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Higher-Order Simulations: Strategic Investment Under Model-Induced Price Patterns

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Abstract

The trading and investment decision processes in financial markets become ever more dependent on the use of valuation and risk models. In the case of risk management for instance, modelling practice has become quite homogeneous and the question arises as to the effect this has on the price formation process. Furthermore, sophisticated investors who have private information about the use and characteristics of these models might be able to make superior gains in such an environment. The aim of this article is to test this hypothesis in a stylised market, where a strategic investor trades on information about the valuation and risk management models used by other market participants. Simulation results show that under certain market conditions, such a 'higher-order' strategy generates higher profits than standard fundamental and momentum strategies that do not draw on information about model use.

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  • Gilbert Peffer & Barbara Llacay, 2007. "Higher-Order Simulations: Strategic Investment Under Model-Induced Price Patterns," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-6.
    • Handle: RePEc:jas:jasssj:2006-23-2
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    Cited by:

    1. Scott Moss, 2007. "Alternative Approaches to the Empirical Validation of Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(1), pages 1-5.

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