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Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics

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Author Info

  • Wolfgang Karl Härdle
  • Nikolaus Hautsch
  • Andrija Mihoci

Abstract

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are modelled using a vector autoregressive model. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model’s forecasting power can be used to improve optimal order execution strategies.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2009-044.

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Length: 35 pages
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:hum:wpaper:sfb649dp2009-044

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Keywords: limit order book; liquidity risk; semiparametric model; factor structure; prediction;

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  1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
  2. Johnson, Timothy C., 2008. "Volume, liquidity, and liquidity risk," Journal of Financial Economics, Elsevier, vol. 87(2), pages 388-417, February.
  3. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
  4. Liu, Wai-Man, 2009. "Monitoring and limit order submission risks," Journal of Financial Markets, Elsevier, vol. 12(1), pages 107-141, February.
  5. Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007. "Time Series Modelling with Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  6. Schmidt, Peter & Phillips, C B Peter, 1992. "LM Tests for a Unit Root in the Presence of Deterministic Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 257-87, August.
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Citations

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Cited by:
  1. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
  2. Robert Engle & Michael Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity, volatility, and flights to safety in the U.S. treasury market: evidence from a new class of dynamic order book models," Staff Reports 590, Federal Reserve Bank of New York.
  3. Wolfgang Karl Härdle,Piotr Majer & Melanie Schienle, 2012. "Yield Curve Modeling and Forecasting using Semiparametric Factor Dynamics," SFB 649 Discussion Papers SFB649DP2012-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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