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Assessing the Risk of Liquidity Suppliers on the Basis of Excess Demand Intensities

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  • Nikolaus Hautsch

Abstract

In this article we introduce the concept of excess volume durations, which are defined as the time until a given amount of buy or sell excess volume is traded on the market. Excess volume durations indicate the one-sided intensity of liquidity demand and characterize the risk of a market maker with respect to asymmetric information and inventory problems. By modeling excess volume durations based on Box--Cox-type autoregressive conditional duration (ACD) models, it is shown that market microstructure variables are predictors for the expected liquidity demand intensity. Moreover, the length of excess volume durations is found to be positively correlated with the magnitude of the corresponding price impact and thus the market depth. , .

Suggested Citation

  • Nikolaus Hautsch, 2003. "Assessing the Risk of Liquidity Suppliers on the Basis of Excess Demand Intensities," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(2), pages 189-215.
  • Handle: RePEc:oup:jfinec:v:1:y:2003:i:2:p:189-215
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    Cited by:

    1. Nikolaus Hautsch & Vahidin Jeleskovic, 2008. "Modelling High-Frequency Volatility and Liquidity Using Multiplicative Error Models," SFB 649 Discussion Papers SFB649DP2008-047, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    3. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," Caepr Working Papers 2007-019, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    4. Aneta Hryckiewicz & Piotr Mielus & Karolina Skorulska & Malgorzata Snarska, 2018. "Does a bank levy increase frictions on the interbank market?," Working Papers 2018-033, Warsaw School of Economics, Collegium of Economic Analysis.
    5. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," CORE Discussion Papers 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 12(1), pages 89-121.
    7. repec:wyi:journl:002120 is not listed on IDEAS

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