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A monitoring procedure for detecting structural breaks in factor copula models

Author

Listed:
  • Manner Hans

    (University of Graz, Institute of Economics, Graz, Austria)

  • Stark Florian
  • Wied Dominik

    (University of Cologne, Institute for Econometrics and Statistics, Albertus-Magnus-Platz, 50923, Cologne, Germany)

Abstract

We propose a new monitoring procedure based on moving sums (MOSUM) for detecting single or multiple structural breaks in factor copula models. The test compares parameter estimates from a rolling window to those from a historical data set and analyzes the behavior under the null hypothesis of no parameter change. The case of multiple breaks is also treated. In the model, the joint copula is given by the copula of random variables which arise from a factor model. This is particularly useful for analyzing high dimensional data. Parameters are estimated with the simulated method of moments (SMM). We analyze the behavior of the monitoring procedure in Monte Carlo simulations and a real data application. We consider an online procedure for predicting the day-ahead Value-at-risk based on the suggested monitoring procedure.

Suggested Citation

  • Manner Hans & Stark Florian & Wied Dominik, 2021. "A monitoring procedure for detecting structural breaks in factor copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(4), pages 171-192, September.
    • Handle: RePEc:bpj:sndecm:v:25:y:2021:i:4:p:171-192:n:1
    DOI: 10.1515/snde-2019-0081
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    Citations

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    Cited by:

    1. Mayer, Alexander & Wied, Dominik, 2023. "Estimation and inference in factor copula models with exogenous covariates," Journal of Econometrics, Elsevier, vol. 235(2), pages 1500-1521.

    More about this item

    Keywords

    factor copula model; monitoring procedure; simulated method of moments; value at risk;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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