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Financial instability from local market measures

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  • Marco Bardoscia
  • Giacomo Livan
  • Matteo Marsili

Abstract

We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. We show that, depending on the number of financial instruments available and on the heterogeneity of local measures, the market moves from an arbitrage-free phase to an unstable one, where the complexity of the market - as measured by the diversity of financial instruments - increases, and arbitrage opportunities arise. A sharp transition separates the two phases. Focusing on two different classes of local measures inspired by real markets strategies, we are able to analytically compute the critical lines, corroborating our findings with numerical simulations.

Suggested Citation

  • Marco Bardoscia & Giacomo Livan & Matteo Marsili, 2012. "Financial instability from local market measures," Papers 1207.0356, arXiv.org, revised Sep 2012.
    • Handle: RePEc:arx:papers:1207.0356
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    References listed on IDEAS

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    1. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2009. "More hedging instruments may destabilize markets," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1912-1928, November.
    2. Claudio Albanese & Toufik Bellaj & Guillaume Gimonet & Giacomo Pietronero, 2011. "Coherent global market simulations and securitization measures for counterparty credit risk," Quantitative Finance, Taylor & Francis Journals, vol. 11(1), pages 1-20.
    3. Raghuram G. Rajan, 2005. "Has financial development made the world riskier?," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, issue Aug, pages 313-369.
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    Cited by:

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    2. Cárdenas, Juan Pablo & Vidal, Gerardo & Urbina, Carolina & Olivares, Gastón & Fuentes, Miguel Angel, 2018. "Social crises. A network model approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 35-48.
    3. Marco Bardoscia & Fabio Caccioli & Juan Ignacio Perotti & Gianna Vivaldo & Guido Caldarelli, 2016. "Distress Propagation in Complex Networks: The Case of Non-Linear DebtRank," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-12, October.

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