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Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management

Author

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  • Jaroslava HLOUSKOVA
  • Kurt SCHMIDHEINY
  • Martin WAGNER

Abstract

The missing wage rigidity in general equilibrium models of efficiency wages is an artifact of the external wage reference perspective conventionally adopted by the literature. Efficiency wage models based on an internal wage reference perspective are capable of generating strong wage rigidity. We propose a structural model of efficiency wages that is broadly consistent with the reported evidence on fairness in labor relations and rent-sharing. Our model provides a robust explanation for wage rigidity and procyclical effort. It also rationalizes reciprocal behavior by workers and the observation that firm productivity is a significant predictor of wage setting.

Suggested Citation

  • Jaroslava HLOUSKOVA & Kurt SCHMIDHEINY & Martin WAGNER, 2004. "Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management," Cahiers de Recherches Economiques du Département d'économie 04.10, Université de Lausanne, Faculté des HEC, Département d’économie.
    • Handle: RePEc:lau:crdeep:04.10
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Carlos Trucíos & Mauricio Zevallos & Luiz K. Hotta & André A. P. Santos, 2019. "Covariance Prediction in Large Portfolio Allocation," Econometrics, MDPI, vol. 7(2), pages 1-24, May.
    2. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    3. Carlos Trucíos & João H. G. Mazzeu & Marc Hallin & Luiz K. Hotta & Pedro L. Valls Pereira & Mauricio Zevallos, 2022. "Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: A General Dynamic Factor Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 40-52, December.
    4. Lahiri, Kajal & Liu, Fushang, 2005. "ARCH models for multi-period forecast uncertainty-a reality check using a panel of density forecasts," MPRA Paper 21693, University Library of Munich, Germany.
    5. Francisco Rubio & Xavier Mestre & Daniel P. Palomar, 2011. "Performance analysis and optimal selection of large mean-variance portfolios under estimation risk," Papers 1110.3460, arXiv.org.
    6. Hlouskova, Jaroslava & Schmidheiny, Kurt & Wagner, Martin, 2009. "Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 330-336, March.

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    More about this item

    Keywords

    multivariate GARCH models; volatility forecasts; portfolio optimization; minimum variance portfolio;
    All these keywords.

    JEL classification:

    • 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
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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