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Original Articles

Integer-valued moving average modelling of the number of transactions in stocks

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Pages 1429-1440 | Published online: 13 Sep 2010

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Kai Yang, Ang Li, Xinyang Yu & Xiaogang Dong. (2023) On MCMC sampling in random coefficients self-exciting integer-valued threshold autoregressive processes. Journal of Statistical Computation and Simulation 0:0, pages 1-19.
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Annika Homburg, Christian H. Weiß, Gabriel Frahm, Layth C. Alwan & Rainer Göb. (2021) Analysis and Forecasting of Risk in Count Processes. Journal of Risk and Financial Management 14:4, pages 182.
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Boris Aleksandrov & Christian H. Weiß. (2019) Parameter estimation and diagnostic tests for INMA(1) processes. TEST 29:1, pages 196-232.
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Dimitris Manolakis, Nicholas Bosowski & Vinay K. Ingle. (2019) Count Time-Series Analysis: A Signal Processing Perspective. IEEE Signal Processing Magazine 36:3, pages 64-81.
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A. M. M. Shahiduzzaman Quoreshi, Reaz Uddin & Naushad Mamode Khan. (2019) Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework. Journal of Risk and Financial Management 12:2, pages 74.
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Christian Weiß. 2018. An Introduction to Discrete-Valued Time Series. An Introduction to Discrete-Valued Time Series 257 274 .
Maria da Conceição Costa, Isabel Pereira & Manuel G. Scotto. 2018. Recent Studies on Risk Analysis and Statistical Modeling. Recent Studies on Risk Analysis and Statistical Modeling 197 212 .
Naushad Mamode Khan, Yuvraj Sunecher & Vandna Jowaheer. (2017) Analyzing the Full BINMA Time Series Process Using a Robust GQL Approach. Journal of Time Series Econometrics 9:2.
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Fukang Zhu, Shuangzhe Liu & Lei Shi. (2016) Local influence analysis for Poisson autoregression with an application to stock transaction data. Statistica Neerlandica 70:1, pages 4-25.
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Maria da Conceição Costa, Manuel G. Scotto & Isabel Pereira. 2016. Time Series Analysis and Forecasting. Time Series Analysis and Forecasting 189 202 .
Manuel G. Scotto, Christian H. Weiß & Sónia Gouveia. (2015) Thinning-based models in the analysis of integer-valued time series: a review. Statistical Modelling 15:6, pages 590-618.
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Mikhail Balaev. (2014) Taking Time Seriously. Sociological Perspectives 58:2, pages 311-330.
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Paul Doukhan & William Kengne. (2015) Inference and testing for structural change in general Poisson autoregressive models. Electronic Journal of Statistics 9:1.
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Magda Monteiro, Manuel G. Scotto & Isabel Pereira. 2015. Dynamics, Games and Science. Dynamics, Games and Science 455 477 .
Vance L. Martin, Andrew R. Tremayne & Robert C. Jung. (2014) EFFICIENT METHOD OF MOMENTS ESTIMATORS FOR INTEGER TIME SERIES MODELS. Journal of Time Series Analysis 35:6, pages 491-516.
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Manuel G. Scotto, Christian H. Weiß, Maria Eduarda Silva & Isabel Pereira. (2014) Bivariate binomial autoregressive models. Journal of Multivariate Analysis 125, pages 233-251.
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Christian H. Weiß & Hee-Young Kim. (2012) Parameter estimation for binomial AR(1) models with applications in finance and industry. Statistical Papers 54:3, pages 563-590.
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Maryam Mohammadipour & John E. Boylan. (2012) Forecast horizon aggregation in integer autoregressive moving average (INARMA) models. Omega 40:6, pages 703-712.
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Fukang Zhu. (2012) Modeling time series of counts with COM-Poisson INGARCH models. Mathematical and Computer Modelling 56:9-10, pages 191-203.
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Ebenezer Afrifa-Yamoah & Ute A. Mueller. (2021) Modeling Digital Camera Monitoring Count Data with Intermittent Zeros for Short-Term Prediction. SSRN Electronic Journal.
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Christian Gouriéroux & Yang Lu. (2019) Noncausal Count Processes. SSRN Electronic Journal.
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