The efficient modelling of high frequency transaction data: A new application of estimating functions in financial economics
This paper investigates the Estimating Function method in the context of ACD modelling and appraises the properties of these estimates. A simulation study is conducted to demonstrate that these estimates are more efficient than the corresponding ML and QML estimates.
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- BAUWENS, Luc & VEREDAS, David, 1999.
"The stochastic conditional duration model: a latent factor model for the analysis of financial durations,"
CORE Discussion Papers
1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
- Allen, David & Lazarov, Zdravetz & McAleer, Michael & Peiris, Shelton, 2009. "Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2535-2555.
- 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.
- Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, Reading University.
- Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.
- Li, David X & Turtle, H J, 2000. "Semiparametric ARCH Models: An Estimating Function Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 174-186, April.
- 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.
- BAUWENS, Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, "undated". "A comparison of financial duration models via density forecasts," CORE Discussion Papers RP 1746, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2004. "A comparison of financial duration models via density forecast," ULB Institutional Repository 2013/136218, ULB -- Universite Libre de Bruxelles.
- Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
- BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," CORE Discussion Papers 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Maria Pacurar, 2008. "Autoregressive Conditional Duration Models In Finance: A Survey Of The Theoretical And Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 711-751, 09.
- Allen, David & Ng, K.H. & Peiris, Shelton, 2013. "Estimating and simulating Weibull models of risk or price durations: An application to ACD models," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 214-225.
- repec:adr:anecst:y:2000:i:60:p:05 is not listed on IDEAS
- 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. Full references (including those not matched with items on IDEAS)
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