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Repeated Time Series Analysis of ARIMA-Noise Models

Author

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  • Wong, Wing-keung
  • Miller, Robert B

Abstract

This article develops a theory and methodology for repeated time series (RTS) measurements on autoregressive integrated moving average-noise (ARIMAN) process. The theory enables us to relax the normality assumption in the ARIMAN model and to identify models for each component series of the process. We discuss the properties, estimation, and forecasting of RTS ARIMAN models and illustrate with examples.

Suggested Citation

  • Wong, Wing-keung & Miller, Robert B, 1990. "Repeated Time Series Analysis of ARIMA-Noise Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 243-250, April.
  • Handle: RePEc:bes:jnlbes:v:8:y:1990:i:2:p:243-50
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    Citations

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    Cited by:

    1. GUORUI BIAN & MICHAEL McALEER & WING-KEUNG WONG, 2013. "Robust Estimation And Forecasting Of The Capital Asset Pricing Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-18.
    2. Guo, Xu & Lam, Kin & Wong, Wing-Keung & Zhu, Lixing, 2012. "A New Pseudo-Bayesian Model of Investors' Behavior in Financial Crises," MPRA Paper 42535, University Library of Munich, Germany.
    3. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    4. Wing-Keung Wong & Meher Manzur & Boon-Kiat Chew, 2003. "How rewarding is technical analysis? Evidence from Singapore stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 543-551.
    5. Wing-Keung Wong & Chenghu Ma, 2008. "Preferences over location-scale family," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 37(1), pages 119-146, October.
    6. Moawia Alghalith & Wing-Keung Wong, 2020. "Extension of Stein's Lemmas to General Functions and Distributions," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(4), pages 77-88, December.
    7. Kai-Yin Woo & Chulin Mai & Michael McAleer & Wing-Keung Wong, 2020. "Review on Efficiency and Anomalies in Stock Markets," Economies, MDPI, vol. 8(1), pages 1-51, March.
    8. Moawia Alghalith & Wing-Keung Wong, 2020. "Extension of Stein's Lemmas to General Functions and Distributions," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(4), pages 77-88, December.
    9. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Management Information, Decision Sciences, and Financial Economics: A Connection," Tinbergen Institute Discussion Papers 18-004/III, Tinbergen Institute.
    10. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    11. Wing-Keung Wong & Boon-Kiat Chew & Douglas Sikorsk, 2001. "Can the Forecasts Generated from E/P Ratio and Bond Yield be Used to Beat Stock Markets?," Multinational Finance Journal, Multinational Finance Journal, vol. 5(1), pages 59-86, March.
    12. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    13. Wong, Wing-Keung & McAleer, Michael, 2009. "Mapping the Presidential Election Cycle in US stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(11), pages 3267-3277.
    14. Kim-Hung Pho & Thi Diem-Chinh Ho & Tuan-Kiet Tran & Wing-Keung Wong, 2019. "Moment Generating Function, Expectation And Variance Of Ubiquitous Distributions With Applications In Decision Sciences: A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 65-150, June.
    15. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.
    16. W. Wong & R. Chan, 2008. "Prospect and Markowitz stochastic dominance," Annals of Finance, Springer, vol. 4(1), pages 105-129, January.
    17. Wing-Keung Wong & Aman Agarwal & Nee-Tat Wong, 2006. "The Disappearing Calendar Anomalies in the Singapore Stock Market," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 11(2), pages 123-139, Jul-Dec.
    18. Meher Manzur & Wing-Keung Wong & Inn-Chau Chee, 1999. "Measuring international competitiveness: experience from East Asia," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1383-1391.
    19. Kim-Hung Pho & Tuan-Kiet Tran & Thi Diem-Chinh Ho & Wing-Keung Wong, 2019. "Optimal Solution Techniques in Decision Sciences A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(1), pages 114-161, March.
    20. Tingting Zou & Shurong Zheng & Zhidong Bai & Jianfeng Yao & Hongtu Zhu, 2022. "CLT for linear spectral statistics of large dimensional sample covariance matrices with dependent data," Statistical Papers, Springer, vol. 63(2), pages 605-664, April.
    21. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    22. Eric S. Fung & Kin Lam & Tak-Kuen Siu & Wing-Keung Wong, 2011. "A Pseudo-Bayesian Model for Stock Returns In Financial Crises," JRFM, MDPI, vol. 4(1), pages 1-31, December.
    23. Wong, Wing-Keung & Bian, Guorui, 2005. "Estimating parameters in autoregressive models with asymmetric innovations," Statistics & Probability Letters, Elsevier, vol. 71(1), pages 61-70, January.
    24. Wong, Wing-Keung & Du, Jun & Chong, Terence Tai-Leung, 2005. "Do the technical indicators reward chartists? A study on the stock markets of China, Hong Kong and Taiwan," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-23.

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