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Market Microstructure During Financial Crisis: Dynamics of Informed and Heuristic-Driven Trading

Author

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  • Mihaly Ormos
  • Dusan Timotity

Abstract

We implement a market microstructure model including informed, uninformed and heuristic-driven investors, which latter behave in line with loss-aversion and mental accounting. We show that the probability of informed trading (PIN) varies significantly during 2008. In contrast, the probability of heuristic-driven trading (PH) remains constant both before and after the collapse of Lehman Brothers. Cross-sectional analysis yields that, unlike PIN, PH is not sensitive to size and volume effects. We show that heuristic-driven traders are universally present in all market segments and their presence is constant over time. Furthermore, we find that heuristic-driven investors and informed traders are disjoint sets.

Suggested Citation

  • Mihaly Ormos & Dusan Timotity, 2016. "Market Microstructure During Financial Crisis: Dynamics of Informed and Heuristic-Driven Trading," Papers 1606.03590, arXiv.org.
    • Handle: RePEc:arx:papers:1606.03590
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    References listed on IDEAS

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    Cited by:

    1. Liu, Hong & Qi, Lina & Li, Zaili, 2019. "Insider trading, representativeness heuristic insider, and market regulation," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 48-64.
    2. Jackowicz, Krzysztof & Kozłowski, Łukasz & Podgórski, Błażej, 2017. "The distant echo of Brexit: Did exporters suffer the most?," Finance Research Letters, Elsevier, vol. 21(C), pages 132-139.
    3. Bikramaditya Ghosh & Krishna MC, 2020. "Econophysical bourse volatility – Global Evidence," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(2), pages 87-107.
    4. Qureshi, Fiza & Kutan, Ali M. & Ismail, Izlin & Gee, Chan Sok, 2017. "Mutual funds and stock market volatility: An empirical analysis of Asian emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 176-192.
    5. Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
    6. Ormos Mihály & Timotity Dusán, 2017. "The Case of “Less is More”: Modelling Risk-Preference with Expected Downside Risk," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 17(2), pages 1-14, June.
    7. Benjamin Carl Anderson & Stoyu I Ivanov, 2019. "Study of the impact of the Great Recession on the relation between earnings surprises and stock returns," Economics Bulletin, AccessEcon, vol. 39(2), pages 1118-1126.
    8. Andor, György & Bohák, András, 2017. "Identifying events in financial time series – A new approach with bipower variation," Finance Research Letters, Elsevier, vol. 22(C), pages 42-48.

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    More about this item

    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

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