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Pair copula constructions in portfolio optimization ploblem

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  • Travkin, Alexandr

    () (Higher School of Economics, Moscow, Russia)

Abstract

The choice and estimation of joint probability distribution function are key steps in portfolio optimization problem. As such distribution functions pair-copula constructions (PCC), or vine-copulae, on arbitrary R-vines are used. For the investor with exponential utility criterion the NYSE oil and gas sector-based portfolios are formed. It is shown, that PCC portfolios gain more profit and also PCCs provide reliable VaR estimates. However, on Russian oil and gas stock market PCC portfolio performance is the weakest among competing portfolios. This could be due to shortcomings of maximal spanning trees procedure, which is commonly used to obtain optimal vine structure.

Suggested Citation

  • Travkin, Alexandr, 2013. "Pair copula constructions in portfolio optimization ploblem," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 32(4), pages 110-133.
  • Handle: RePEc:ris:apltrx:0226
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    References listed on IDEAS

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    Cited by:

    1. Penikas, Henry, 2014. "Investment portfolio risk modelling based on hierarchical copulas," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 35(3), pages 18-38.

    More about this item

    Keywords

    pair copula constructions; regular vines; EGARCH; portfolio optimization; expected utility; VaR;

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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