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A Discrete-State Continuous-Time Model of Financial Transactions Prices and Times: The Autoregressive Conditional Multinomial-Autoregressive Conditional Duration Model

Citations

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Cited by:

  1. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
  2. Hansen, Peter Reinhard, 2015. "A martingale decomposition of discrete Markov chains," Economics Letters, Elsevier, vol. 133(C), pages 14-18.
  3. Bhatti, Chad R., 2009. "On the interday homogeneity in the intraday rate of trading," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2250-2257.
  4. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
  5. 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.
  6. Jannik Schütz Roungkvist & Peter Enevoldsen & George Xydis, 2020. "High-Resolution Electricity Spot Price Forecast for the Danish Power Market," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
  7. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
  8. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
  9. Dionne, Georges & Zhou, Xiaozhou, 2016. "The Dynamics of Ex-ante High-Frequency Liquidity: An Empirical Analysis," Working Papers 15-5, HEC Montreal, Canada Research Chair in Risk Management.
  10. Stanislav Anatolyev & Dmitry Shakin, 2007. "Trade intensity in the Russian stock market: dynamics, distribution and determinants," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 87-104.
  11. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
  12. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
  13. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578.
  14. Moysiadis, Theodoros & Fokianos, Konstantinos, 2014. "On binary and categorical time series models with feedback," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 209-228.
  15. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2017. "Nonparametric estimation of dynamic discrete choice models for time series data," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 97-120.
  16. Poutré, Cédric & Dionne, Georges & Yergeau, Gabriel, 2024. "The profitability of lead–lag arbitrage at high frequency," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1002-1021.
  17. Kalaitzoglou, Iordanis Angelos & Ibrahim, Boulis Maher, 2015. "Liquidity and resolution of uncertainty in the European carbon futures market," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 89-102.
  18. Georges Dionne & Xiaozhou Zhou, 2020. "The dynamics of ex-ante weighted spread: an empirical analysis," Quantitative Finance, Taylor & Francis Journals, vol. 20(4), pages 593-617, April.
  19. Liu, Shouwei & Tse, Yiu-Kuen, 2015. "Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach," Journal of Econometrics, Elsevier, vol. 189(2), pages 437-446.
  20. Florian Ielpo & Dominique Gúegan, 2009. "Understanding the Importance of the Duration and Size of the Variations of Fed’s Target Rate," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(3-4), pages 44-72, August.
  21. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
  22. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
  23. 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, Oxford University Press, vol. 12(1), pages 89-121.
  24. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
  25. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
  26. repec:hum:wpaper:sfb649dp2011-044 is not listed on IDEAS
  27. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
  28. Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
  29. Charlie X. Cai & Qi Zhang, 2016. "High†Frequency Exchange Rate Forecasting," European Financial Management, European Financial Management Association, vol. 22(1), pages 120-141, January.
  30. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
  31. Duan, Qihong & Wei, Ying & Chen, Zhiping, 2014. "Relationship between the benchmark interest rate and a macroeconomic indicator," Economic Modelling, Elsevier, vol. 38(C), pages 220-226.
  32. Qi Zhang & Charlie X Cai & Kevin Keasey, 2009. "Forecasting using high-frequency data: a comparison of asymmetric financial duration models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 371-386.
  33. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
  34. Nolte, Ingmar & Nolte, Sandra & Pohlmeier, Winfried, 2019. "What determines forecasters’ forecasting errors?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 11-24.
  35. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
  36. 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.
  37. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
  38. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Marked Hawkes process modeling of price dynamics and volatility estimation," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 174-200.
  39. Ng, Wing Lon, 2006. "Overreaction and multiple tail dependence at the high-frequency level: The copula rose," SFB 649 Discussion Papers 2006-086, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  40. Erhard Reschenhofer & Manveer Kaur Mangat & Christian Zwatz & Sándor Guzmics, 2020. "Evaluation of current research on stock return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 334-351, March.
  41. Christian M. Hafner, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1363-1379, December.
  42. Wei Wei & Denis Pelletier, 2015. "A Jump-Diffusion Model with Stochastic Volatility and Durations," CREATES Research Papers 2015-34, Department of Economics and Business Economics, Aarhus University.
  43. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2009. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 777-792, December.
  44. repec:hum:wpaper:sfb649dp2006-086 is not listed on IDEAS
  45. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
  46. 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.
  47. Emilio Abad-Segura & Mariana-Daniela González-Zamar, 2020. "Global Research Trends in Financial Transactions," Mathematics, MDPI, vol. 8(4), pages 1-32, April.
  48. Francisco Blasques & Vladim'ir Hol'y & Petra Tomanov'a, 2018. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Papers 1812.07318, arXiv.org, revised May 2024.
  49. Dungey, Mardi & Jeyasreedharan, Nagaratnam & Li, Tuo, 2010. "Modelling the Time Between Trades in the After-Hours Electronic Equity Futures Market," Working Papers 10451, University of Tasmania, Tasmanian School of Business and Economics, revised 30 May 2012.
  50. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
  51. Renault, Eric & van der Heijden, Thijs & Werker, Bas J.M., 2014. "The dynamic mixed hitting-time model for multiple transaction prices and times," Journal of Econometrics, Elsevier, vol. 180(2), pages 233-250.
  52. Nyberg, Henri, 2011. "Forecasting the direction of the US stock market with dynamic binary probit models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 561-578, April.
  53. 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.
  54. Fokianos, Konstantinos & Truquet, Lionel, 2019. "On categorical time series models with covariates," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3446-3462.
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