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Prediction Regions for Interval-valued Time Series

Author

Listed:
  • Gloria Gonzalez-Rivera

    (Department of Economics, University of California Riverside)

  • Yun Luo

  • Esther Ruiz

    (Universidad Carlos III de Madrid)

Abstract

We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fi tting a possibly non-Gaussian bivariate VAR model to the center/log-range system, we transform prediction regions (analytical and bootstrap) for this system into regions for center/range and upper/lower bounds systems. Monte Carlo simulations show that bootstrap methods are preferred according to several new metrics. For daily S&P500 low/high returns, we build joint conditional prediction regions of the return level and volatility. We illustrate the usefulness of obtaining bootstrap forecasts regions for low/high returns by developing a trading strategy and showing its pro fitability when compared to using point forecasts.

Suggested Citation

  • Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
  • Handle: RePEc:ucr:wpaper:201921
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    File URL: https://economics.ucr.edu/repec/ucr/wpaper/201921.pdf
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    Cited by:

    1. is not listed on IDEAS
    2. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    3. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    4. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
    5. Yun Luo & Gloria González-Rivera, 2024. "A Truncated Mixture Transition Model for Interval-Valued Time Series," Journal of Financial Econometrics, Oxford University Press, vol. 22(4), pages 1130-1169.
    6. Xingyu Dai & Roy Cerqueti & Qunwei Wang & Ling Xiao, 2025. "Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series," Annals of Operations Research, Springer, vol. 348(1), pages 735-775, May.
    7. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.

    More about this item

    Keywords

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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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