A Truncated Mixture Transition Model for Interval-Valued Time Series

Yun Luo and Gloria González-Rivera

Journal of Financial Econometrics, 2024, vol. 22, issue 4, 1130-1169

Abstract: We propose a model for interval-valued time series that specifies 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 expectation maximization (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: EM algorithm; interval-valued data; mixture transition model; truncated normal distribution (search for similar items in EconPapers)
JEL-codes: C01 C32 C34 (search for similar items in EconPapers)
Date: 2024
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