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Asset Allocation with Markovian Regime Switching: Efficient Frontier and Tangent Portfolio with Regime Switching

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  • Oliveira, André Barbosa
  • Valls Pereira, Pedro Luiz

Abstract

A alocação de portfólio é importante na gestão de riscos e realização de ganhos no mercado financeiro. A alocação de ativos é uma tomada de decisão sob incerteza baseada em métodos estatísticos. Os retornos dos ativos financeiros geralmente apresentam mudança de regime, com distribuição dos retornos diferente nos períodos de normalidade e crise. A mudança de regime no processo gerador dos retornos torna necessário reformular o problema de alocação de portfólio. Este trabalho desenvolve modelos de alocação de portfólio com mudança de regime. Como resultado do estudo comparativo de alocação de ativos os portfólios com mudança de regime permitem aumentar o espaço de risco e retorno, diminuindo o risco para cada nível de retornos da fronteira eficiente média variância, e possuem melhor relação risco e retorno dos rendimentos no tempo.

Suggested Citation

  • Oliveira, André Barbosa & Valls Pereira, Pedro Luiz, 2018. "Asset Allocation with Markovian Regime Switching: Efficient Frontier and Tangent Portfolio with Regime Switching," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(1), May.
  • Handle: RePEc:sbe:breart:v:38:y:2018:i:1:a:66264
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    1. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    5. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
    6. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    7. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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