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We propose an early warning system for financial crisis prediction, which is tailored to longitudinal data with missing values and time-varying covariates. The proposed system is based on a hidden Markov model that includes selected time-varying economic drivers and the lagged response variable, thus relaxing the local independence assumption. Partially missing outcomes at a given time are considered under the missing-at-random assumption, and partially missing values on the covariates are accounted for by dummy indicators. We study in-sample and out-of-sample model performance in terms of forecasting, considering an application related to country-level financial crises.

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Prediction of Early Warning Crises by a Hidden Markov Model with Covariates

  • 会议论文

  • 发表日期：

    2025年

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  • Luca Brusa,
  • Fulvia Pennoni,
  • Francesco Bartolucci,
  • Romina Peruilh Bagolini

摘要

We propose an early warning system for financial crisis prediction, which is tailored to longitudinal data with missing values and time-varying covariates. The proposed system is based on a hidden Markov model that includes selected time-varying economic drivers and the lagged response variable, thus relaxing the local independence assumption. Partially missing outcomes at a given time are considered under the missing-at-random assumption, and partially missing values on the covariates are accounted for by dummy indicators. We study in-sample and out-of-sample model performance in terms of forecasting, considering an application related to country-level financial crises.