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Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model

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  2. Loaiza-Maya, Rubén & Nibbering, Didier & Zhu, Dan, 2024. "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Journal of Econometrics, Elsevier, vol. 241(2).
  3. Kang, Yao & Zhang, Yuqing & Wang, Shuhui & Zhao, Zhiwen, 2025. "A new class of Z-valued INAR(1) models with application to mutual fund flows," Economics Letters, Elsevier, vol. 252(C).
  4. Aknouche, Abdelhakim & Gouveia, Sónia & Scotto, Manuel G., 2026. "Random multiplication versus random sum: Autoregressive-like models with integer-valued random inputs," Computational Statistics & Data Analysis, Elsevier, vol. 217(C).
  5. Paolo Gorgi, 2020. "Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1325-1347, December.
  6. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.
  7. Leopoldo Catania & Roberto Di Mari & Paolo Santucci de Magistris, 2022. "Dynamic Discrete Mixtures for High-Frequency Prices," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 559-577, April.
  8. Matteo Iacopini & Carlo R.M.A. Santagiustina, 2021. "Filtering the intensity of public concern from social media count data with jumps," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1283-1302, October.
  9. Lange, Rutger-Jan, 2024. "Bellman filtering and smoothing for state–space models," Journal of Econometrics, Elsevier, vol. 238(2).
  10. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
  11. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
  12. Vladimír Holý, 2026. "An intraday GARCH model for discrete price changes and irregularly spaced observations," Annals of Operations Research, Springer, vol. 357(1), pages 301-345, February.
  13. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
  14. Aknouche, Abdelhakim & Francq, Christian & Goto, Yuichi, 2026. "Mixed difference integer-valued GARCH model for Z-valued time series," MPRA Paper 128358, University Library of Munich, Germany.
  15. Morier, Bruno & Valls Pereira, Pedro L., 2025. "Forecasting intraday volatility and densities using deep learning," The Quarterly Review of Economics and Finance, Elsevier, vol. 104(C).
  16. Baena-Mirabete, S. & Puig, P., 2020. "Computing probabilities of integer-valued random variables by recurrence relations," Statistics & Probability Letters, Elsevier, vol. 161(C).
  17. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
  18. 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.
  19. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
  20. Holý, Vladimír, 2025. "The pitfalls of continuous heavy-tailed distributions in high-frequency data analysis," Finance Research Letters, Elsevier, vol. 86(PE).
  21. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
  22. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
  23. Kung, Ko-Lun & Liu, I-Chien & Wang, Chou-Wen, 2021. "Modeling and pricing longevity derivatives using Skellam distribution," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 341-354.
  24. Xiaofei Hu & Beth Andrews, 2021. "Integer‐valued asymmetric garch modeling," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 737-751, September.
  25. Carallo, Giulia & Casarin, Roberto & Robert, Christian P., 2024. "Generalized Poisson difference autoregressive processes," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1359-1390.
  26. Zhanyu Chen & Kai Zhang & Hongbiao Zhao, 2022. "A Skellam market model for loan prime rate options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 525-551, March.
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