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Convex incentives in financial markets: an agent-based analysis

Author

Listed:
  • Annalisa Fabretti

    (University of Rome)

  • Tommy Gärling

    (University of Gothenburg)

  • Stefano Herzel

    (University of Rome)

  • Martin Holmen

    (University of Gothenburg)

Abstract

We investigate whether convex incentive contracts are a source of instability of financial markets as indicated by the results of a continuous double-auction asset market experiment performed by Holmen et al. (J Econ Dyn Control 40:179–194, 2014). We develop a model to replicate the setting of the experiment and perform an agent-based simulation where agents have linear or convex incentives. Extending the simulation by varying features of actual asset markets that were not studied in the experiment, our main results show that increasing the number of convex incentive contracts increases prices and volatility and decreases market liquidity, measured both as bid–ask spreads and volumes. We also observe that the influence of risk aversion on traders’ decisions decreases when there are convex contracts and that increasing the differences in initial wealth among the traders has similar effects as increasing number of convex incentive contracts.

Suggested Citation

  • Annalisa Fabretti & Tommy Gärling & Stefano Herzel & Martin Holmen, 2017. "Convex incentives in financial markets: an agent-based analysis," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 375-395, November.
    • Handle: RePEc:spr:decfin:v:40:y:2017:i:1:d:10.1007_s10203-017-0200-1
    DOI: 10.1007/s10203-017-0200-1
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    More about this item

    Keywords

    Incentives; Market instability; Agent-based simulations;
    All these keywords.

    JEL classification:

    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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