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Modelling Intraday Trading Activity Using Box-Cox-ACD Models

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  • Hautsch, Nikolaus

Abstract

In this paper, I model the intraday trading activity based on volume durations, i.e. the waiting time until a predetermined volume is absorbed by the market. Since this concept measures the trading volume per time it is strongly related to market liquidity. I focus on volumes measured independently of the side of the market as well as on buy volumes, sell volumes and volumes measured on both market sides simultaneously. For econometric modelling of the different duration concepts, the performance of alternative types of Box-Cox-ACD models are analyzed. By evaluating out-of-sample forecasts, evidence is provided that Box-Cox-ACD models are a valuable tool for predicting volume durations. It is shown that volume durations measured independently of the side of the market have the best predictability. Furthermore, I illustrate that the inclusion of explanatory variables capturing past market activities concerning the price process and imbalances between the buy and sell side of the market. The empirical study uses IBM transaction data from the NYSE.

Suggested Citation

  • Hautsch, Nikolaus, 2002. "Modelling Intraday Trading Activity Using Box-Cox-ACD Models," CoFE Discussion Papers 02/05, University of Konstanz, Center of Finance and Econometrics (CoFE).
    • Handle: RePEc:zbw:cofedp:0205
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    1. David Veredas & Juan Rodriguez-Poo & Antoni Espasa, 2001. "On the (Intradaily) Seasonality and Dynamics of a Financial Point Process : A Semiparametric Approach," Working Papers 2001-19, Center for Research in Economics and Statistics.
    2. Raj Aggarwal & Edward Gruca, 1993. "Intraday Trading Patterns In The Equity Options Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 16(4), pages 285-297, December.
    3. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    4. Elyasiani, Elyas & Hauser, Shmuel & Lauterbach, Beni, 2000. "Market Response to Liquidity Improvements: Evidence from Exchange Listings," The Financial Review, Eastern Finance Association, vol. 35(1), pages 1-14, February.
    5. Al-Suhaibani, Mohammad & Kryzanowski, Lawrence, 2000. "An exploratory analysis of the order book, and order flow and execution on the Saudi stock market," Journal of Banking & Finance, Elsevier, vol. 24(8), pages 1323-1357, August.
    6. Keim, Donald B & Madhaven, Ananth, 1996. "The Upstairs Market for Large-Block Transactions: Analysis and Measurement of Price Effects," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 1-36.
    7. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    8. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    9. repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
    10. Kluger, Brian D & Stephan, Jens, 1997. "Alternative Liquidity Measures and Stock Returns," Review of Quantitative Finance and Accounting, Springer, vol. 8(1), pages 19-36, January.
    11. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
    12. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    13. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    14. Glosten, Lawrence R, 1987. "Components of the Bid-Ask Spread and the Statistical Properties of Transaction Prices," Journal of Finance, American Finance Association, vol. 42(5), pages 1293-1307, December.
    15. Bessembinder, Hendrik, 2000. "Tick Size, Spreads, and Liquidity: An Analysis of Nasdaq Securities Trading near Ten Dollars," Journal of Financial Intermediation, Elsevier, vol. 9(3), pages 213-239, July.
    16. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    17. Nikolaus Hautsch, 1999. "Analyzing the Time between Trades with a Gamma Compounded Hazard Model. An Application to LIFFE Bund Future Transactions," Finance 9904002, University Library of Munich, Germany.
    18. Fernandes, Marcelo & Grammig, Joachim, 2006. "A family of autoregressive conditional duration models," Journal of Econometrics, Elsevier, vol. 130(1), pages 1-23, January.
    19. George, Thomas J & Kaul, Gautam & Nimalendran, M, 1991. "Estimation of the Bid-Ask Spread and Its Components: A New Approach," Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 623-656.
    20. Robert F. Engle & Joe Lange, 1997. "Measuring, Forecasting and Explaining Time Varying Liquidity in the Stock Market," NBER Working Papers 6129, National Bureau of Economic Research, Inc.
    21. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. "An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    22. Finucane, Thomas J., 2000. "A Direct Test of Methods for Inferring Trade Direction from Intra-Day Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 553-576, December.
    23. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    24. Foster, F Douglas & Viswanathan, S, 1993. "The Effect of Public Information and Competition on Trading Volume and Price Volatility," Review of Financial Studies, Society for Financial Studies, vol. 6(1), pages 23-56.
    25. Easley, David & O'Hara, Maureen, 1991. "Order Form and Information in Securities Markets," Journal of Finance, American Finance Association, vol. 46(3), pages 905-927, July.
    26. Jason Greene & Scott Smart, 1999. "Liquidity Provision and Noise Trading: Evidence from the “Investment Dartboard” Column," Journal of Finance, American Finance Association, vol. 54(5), pages 1885-1899, October.
    27. 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.
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    Citations

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    Cited by:

    1. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.
    2. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    3. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    4. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    5. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    6. Wing Lon Ng, 2010. "Dynamic Order Submission And Herding Behavior In Electronic Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 27-43, March.

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    More about this item

    Keywords

    volume durations; liquidity concepts; Generalized F distribution; out-of-sample-forecasts;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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