IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v19y2019i9p1473-1489.html
   My bibliography  Save this article

Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics

Author

Listed:
  • Ying Chen
  • Wee Song Chua
  • Wolfgang Karl Härdle

Abstract

We develop a dynamic model to simultaneously characterize the liquidity demand and supply in a limit order book. The joint dynamics are modeled in a unified Vector Functional AutoRegressive (VFAR) framework. We derive a closed-form maximum likelihood estimator under sieves and establish asymptotic consistency of the proposed method under mild conditions. We find the VFAR model presents strong interpretability and accurate out-of-sample forecasts. In application to limit order book records of 12 stocks in the NASDAQ, traded from 2 January 2015 to 6 March 2015, the VFAR model yields $R^2 $R2 values as high as 98.5% for in-sample estimation and 98.2% in out-of-sample forecast experiments. It produces accurate 5-, 25- and 50-min forecasts, with RMSE as low as 0.09–0.58 and MAPE as low as 0.3–4.5%. The predictive power stably reduces trading cost in the order splitting strategies and achieves excess gains of 31 basis points on average.

Suggested Citation

  • Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
    • Handle: RePEc:taf:quantf:v:19:y:2019:i:9:p:1473-1489
    DOI: 10.1080/14697688.2019.1622290
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2019.1622290
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2019.1622290?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Benston, George J. & Hagerman, Robert L., 1974. "Determinants of bid-asked spreads in the over-the-counter market," Journal of Financial Economics, Elsevier, vol. 1(4), pages 353-364, December.
    2. Gur Huberman & Dominika Halka, 2001. "Systematic Liquidity," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 24(2), pages 161-178, June.
    3. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    4. Peter Gomber & Uwe Schweickert & Erik Theissen, 2015. "Liquidity Dynamics in an Electronic Open Limit Order Book: an Event Study Approach," European Financial Management, European Financial Management Association, vol. 21(1), pages 52-78, January.
    5. Umut Çetin & Robert A. Jarrow & Philip Protter, 2008. "Liquidity risk and arbitrage pricing theory," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 8, pages 153-183, World Scientific Publishing Co. Pte. Ltd..
    6. Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
    7. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    8. Stoll, Hans R, 1978. "The Pricing of Security Dealer Services: An Empirical Study of NASDAQ Stocks," Journal of Finance, American Finance Association, vol. 33(4), pages 1153-1172, September.
    9. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    10. Mourid, Tahar & Bensmain, Nawel, 2006. "Sieves estimator of the operator of a functional autoregressive process," Statistics & Probability Letters, Elsevier, vol. 76(1), pages 93-108, January.
    11. Philippe C. Besse & Herve Cardot & David B. Stephenson, 2000. "Autoregressive Forecasting of Some Functional Climatic Variations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 673-687, December.
    12. Antoniadis, Anestis & Sapatinas, Theofanis, 2003. "Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 133-158, October.
    13. Guillas, Serge, 2001. "Rates of convergence of autocorrelation estimates for autoregressive Hilbertian processes," Statistics & Probability Letters, Elsevier, vol. 55(3), pages 281-291, December.
    14. Kerry Cooper, S. & Groth, John C. & Avera, William E., 1985. "Liquidity, exchange listing, and common stock performance," Journal of Economics and Business, Elsevier, vol. 37(1), pages 19-33, February.
    15. Huberman, Gur & Halka, Dominika, 2001. "Systematic Liquidity," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 24(2), pages 161-178, Summer.
    16. Michael J. Fleming & Eli M. Remolona, 1999. "Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information," Journal of Finance, American Finance Association, vol. 54(5), pages 1901-1915, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:hum:wpaper:sfb649dp2016-025 is not listed on IDEAS
    2. Tarun Chordia & Asani Sarkar & Avanidhar Subrahmanyam, 2003. "An empirical analysis of stock and bond market liquidity," Staff Reports 164, Federal Reserve Bank of New York.
    3. Chordia, Tarun & Sarkar, Asani & Subrahmanyam, Avanidhar, 2005. "The Joint Dynamics of Liquidity, Returns, and Volatility Across Small and Large Firms," University of California at Los Angeles, Anderson Graduate School of Management qt6z81z2wc, Anderson Graduate School of Management, UCLA.
    4. Sensoy, Ahmet, 2019. "Commonality in ask-side vs. bid-side liquidity," Finance Research Letters, Elsevier, vol. 28(C), pages 198-207.
    5. K. Lebedeva, 2015. "An Empirical Analysis of the Russian Financial Markets’ Liquidity and Returns," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(3), pages 5-31.
    6. Zintle Twala & Riza Demirer & Rangan Gupta, 2018. "Does Liquidity Risk Explain the Time-Variation in Asset Correlations? Evidence from Stocks, Bonds and Commodities," Journal of Economics and Behavioral Studies, AMH International, vol. 10(2), pages 120-132.
    7. Lee, Jie-Haun & Lin, Shu-Ying & Lee, Wan-Chen & Tsao, Chueh-Yung, 2006. "Common factors in liquidity: Evidence from Taiwan's OTC stock market," International Review of Financial Analysis, Elsevier, vol. 15(4-5), pages 306-327.
    8. Tarun Chordia & Asani Sarkar & Avanidhar Subrahmanyam, 2001. "Common determinants of bond and stock market liquidity: the impact of financial crises, monetary policy, and mutual fund flows," Staff Reports 141, Federal Reserve Bank of New York.
    9. Xu, Yongdeng & Taylor, Nick & Lu, Wenna, 2018. "Illiquidity and volatility spillover effects in equity markets during and after the global financial crisis: An MEM approach," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 208-220.
    10. O’Sullivan, Conall & Papavassiliou, Vassilios G. & Wafula, Ronald Wekesa & Boubaker, Sabri, 2024. "New insights into liquidity resiliency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
    11. Kale, Jayant R. & Loon, Yee Cheng, 2011. "Product market power and stock market liquidity," Journal of Financial Markets, Elsevier, vol. 14(2), pages 376-410, May.
    12. Schneider, Michael & Lillo, Fabrizio & Pelizzon, Loriana, 2016. "How has sovereign bond market liquidity changed? An illiquidity spillover analysis," SAFE Working Paper Series 151, Leibniz Institute for Financial Research SAFE.
    13. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    14. O’Sullivan, Conall & Papavassiliou, Vassilios G., 2020. "On the term structure of liquidity in the European sovereign bond market," Journal of Banking & Finance, Elsevier, vol. 114(C).
    15. Keunkwan Ryu & Hyun-yeol Shin, 2010. "Liquidity as Price Effect on Time to Sale," Korean Economic Review, Korean Economic Association, vol. 26, pages 307-340.
    16. Hadhri, Sinda & Ftiti, Zied, 2019. "Commonality in liquidity among Middle East and North Africa emerging stock markets: Does it really matter?," Economic Systems, Elsevier, vol. 43(3).
    17. Berhoune, Kamila & Bensmain, Nawel, 2018. "Sieves estimator of functional autoregressive process," Statistics & Probability Letters, Elsevier, vol. 135(C), pages 60-69.
    18. Haugom, Erik & Ray, Rina, 2017. "Heterogeneous traders, liquidity, and volatility in crude oil futures market," Journal of Commodity Markets, Elsevier, vol. 5(C), pages 36-49.
    19. Richter, Thomas Julian, 2022. "Liquidity commonality in sovereign bond markets," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 501-518.
    20. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    21. Ying Chen & Bo Li, 2017. "An Adaptive Functional Autoregressive Forecast Model to Predict Electricity Price Curves," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 371-388, July.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:quantf:v:19:y:2019:i:9:p:1473-1489. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.