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Reconstructing Agents’ Strategies from Price Behavior

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Abstract

In the past years several Agents Based Models (ABMs) have been introduced to reproduce and interpret the main features of financial markets [7,14]. The ABMs go beyond simple differential equations with the aim of being able to address the complex phenomenology of a dynamics. This phenomenology is usually interpreted in terms of the Stylized Facts (SF) which correspond to complex correlations beyond the simple Random Walk (RW). The ABMs give the possibility to describe the intrinsic heterogeneity of the market which seems to be responsible for many of these SF [6, 12]. The main SF are the fat tails for the fluctuations of price-returns, the arbitrage condition, which implies no correlations in the price returns, and the volatility clustering which implies long memory correlations for volatility.

Keywords

  • Stylize Fact
  • Price Return
  • Price Behavior
  • Minimal Agent
  • Reconstruction Analysis

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Alfi, V., Cristelli, M., Pietronero, L., Zaccaria, A. (2011). Reconstructing Agents’ Strategies from Price Behavior. In: Abergel, F., Chakrabarti, B.K., Chakraborti, A., Mitra, M. (eds) Econophysics of Order-driven Markets. New Economic Windows. Springer, Milano. https://doi.org/10.1007/978-88-470-1766-5_8

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