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Modeling, Risk Assessment and Portfolio Optimization of Energy Futures

Modeling, Risk Assessment and Portfolio Optimization of Energy Futures,Almira Biglova,Takashi Kanamura,Svetlozar T. Rachev,Stoyan Stoyanov

Modeling, Risk Assessment and Portfolio Optimization of Energy Futures   (Citations: 4)
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This paper examines the portfolio optimization of energy futures by using the STARR ratio that can evaluate the risk and return relationship for skewed distributed returns. We model the price returns for energy futures by using the ARMA(1,1)- GARCH(1,1)-PCA model with stable distributed innovations that reflects the charac- teristics of energy: mean reversion, heteroskedasticity, seasonality, and spikes. Then, we propose the method for selecting the portfolio of energy futures by maximizing the STARR ratio, what we call "Winner portfolio". The empirical studies by using energy futures of WTI crude oil, heating oil, and natural gas traded on the NYMEX compare the price return models with stable distributed innovations to those with normal ones. We show that the models with stable ones are more appropriate for energy futures than those with normal ones. In addition, we discuss what characteristics of energy futures cause the stable distributed innovations in the returns. Then, we generate the price returns of energy futures using the ARMA(1,1)-GARCH(1,1)-PCA model with stable ones and choose the portfolio of energy futures employing the generated price returns. The results suggest that the selected portfolio of "Winner portfolio" perform better than the average weighted portfolio of "Loser portfolio". Finally, we examine the usefulness of the STARR ratio to select the winner portfolio of energy futures.
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    • ...In particular, we assume the marginals evolve as an ARMA(0,2)-GARCH(0,2) model with stable paretian residuals and the joint distribution of residuals is estimated with an asymmetric t-copula...
    • ...In particular, we assume the marginals evolve as an ARMA(0,2)-GARCH(0,2) model with stable paretian residuals and the joint distribution of residuals is estimated with an asymmetric t-copula...
    • ...� Step 8 Once we have described the multivariate behavior of standardized innovation at time T+1 using relation (2) we can generate S scenario of the vector of innovation " (s)...
    • ...From this preliminary analysys we deduce that the above asset returns are well approximated by an ARMA(2,0)-GARCH(0,2) model...
    • ...From this preliminary analysys we deduce that the above asset returns are well approximated by an ARMA(2,0)-GARCH(0,2) model...
    • ...That is, for each series (j = 1;:::;5) the formulas (1, 2, 3) are represented by:...

    Sergio Ortobelliet al. PORTFOLIO SELECTION BASED ON A SIMULATED COPULA

    • ...Biglova et al. (2008 )u se at-copula to capture the dependence...
    • ...More recently, Biglova et al. (2008) have argued that characteristics such as mean reversion should be incorporated in modeling energy prices...
    • ...As there is mixed evidence of mean reversion for crude oil (Biglova et al. 2008; Dias 2004; Paddock et al. 1988), for generality, we incorporate this feature in the proposed copula model...

    Hemantha S. B. Herathet al. Crack spread option pricing with copulas

    • ...3 See Sun et al. (2008) and Biglova et al. (2008)...
    • ...14 See among others, Chopra and Ziemba (1993), Papp et al. (2005), Kondor et al. (2007), Rachev et al. (2005), Sun et al. (2008), and Biglova et al. (2008))...
    • ...See, among others, Rachev et al. (2005), Sun et al. (2008), Biglova et al. (2008), and Cherubini et al. (2004) for the definition of some classical copula used in finance literature...

    Almira Biglovaet al. Modeling, Estimation, and Optimization of Equity Portfolios with Heavy...

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