A Truncated Mixture Transition Model for Interval-valued Time Series

Gloria Gonzalez-Rivera and Yun Luo
Additional contact information
Yun Luo: Monmouth University

No 202315, Working Papers from University of California at Riverside, Department of Economics

Abstract: We propose a model for interval-valued time series that specifi es the conditional joint distribution of the upper and lower bounds as a mixture of truncated bivariate normal distributions. It preserves the interval natural order and provides great flexibility on capturing potential conditional heteroscedasticity and non-Gaussian features. The standard EM algorithm applied to truncated mixtures does not provide a closed-form solution in the M step. A new EM algorithm solves this problem. The model applied to the interval-valued IBM daily stock returns exhibits superior performance over competing models in-sample and out-of-sample evaluation. A trading strategy showcases the usefulness of our approach.

Keywords: interval-valued data; mixture transition model; EM algorithm; truncated normal distribution. (search for similar items in EconPapers)
JEL-codes: C01 C32 C34 (search for similar items in EconPapers)
Pages: 72 Pages
Date: 2023-07
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Forthcoming in Journal of Financial Econometrics

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https://economics.ucr.edu/repec/ucr/wpaper/202315.pdf First version, 2023 (application/pdf)

Related works:
Working Paper: A Truncated Mixture Transition Model for Interval-valued Time Series (2020)
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