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Global Risk Evolution and Diversification: a Copula-DCC-GARCH Model Approach

Author

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  • Marcelo Brutti Righi

    (Universidade Federal de Santa Maria)

  • Paulo Sergio Ceretta

Abstract

In this paper we estimate a dynamic portfolio composed by the U.S., German, British, Brazilian, Hong Kong and Australian markets, the period considered started on September 2001 and finished in September 2011. We ran the Copula-DCC-GARCH model on the daily returns conditional covariance matrix. The results allow us to conclude that there were changes in portfolio composition, occasioned by modifications in volatility and dependence between markets. The dynamic approach significantly reduced the portfolio risk if compared to the traditional static approach, especially in turbulent periods. Furthermore, we verified that the estimated copula model outperformed the conventional DCC model for the sample studied.

Suggested Citation

  • Marcelo Brutti Righi & Paulo Sergio Ceretta, 2012. "Global Risk Evolution and Diversification: a Copula-DCC-GARCH Model Approach," Brazilian Review of Finance, Brazilian Society of Finance, vol. 10(4), pages 529-550.
    • Handle: RePEc:brf:journl:v:10:y:2012:i:4:p:529-550
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    Cited by:

    1. Ahsan Abbas & Eatzaz Ahmed & Fazal Husain, 2019. "Political and Economic Uncertainty and Investment Behaviour in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 58(3), pages 307-331.

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    More about this item

    Keywords

    Dynamic Portfolio; Risk Management; Copulas; Multivariate GARCH;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • 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

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