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Performance Analysis of Portfolio Optimisation Strategies: Evidence from the Exchange Market

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  • Jason Narsoo

Abstract

Portfolio allocation is embedded in many decisional tasks for ensuring best returns under the constraint of minimising risk. In this paper, we implement several strategies in order to generate a holistic assessment of portfolio evaluation. The study analyses the performance of an extended framework of the classical tangency and targeted portfolio strategies. The extension is essentially the use of the skewed student-t distribution for the individual assets¡¯ log-return. Our investigation is based on 15 currencies with US dollar as the base currency for the period spanning from 1999 to 2015. A comparative performance analysis between the portfolio optimization strategies is undertaken on the basis of various performance measures, namely the portfolio expected return, standard deviation, Beta coefficient, Sharpe Ratio, Jensen¡¯s Alpha, Treynor ratio and Roy ratio. The portfolio VaR being perceived as one of the core metrics for risk management is also computed. It is actually proxied by 5 VaR estimates - the parametric Gaussian, the equally-weighted historical VaR, the bootstrapping historical VaR, the Monte-Carlo simulation VaR and the parametric GHD VaR. The results show that both tangency portfolios, with the Gaussian or the skewed student-t distribution perform best, particularly on the basis of highest Sharpe reward-to-variability ratio and lowest Value-at-Risk.

Suggested Citation

  • Jason Narsoo, 2017. "Performance Analysis of Portfolio Optimisation Strategies: Evidence from the Exchange Market," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(6), pages 124-132, June.
    • Handle: RePEc:ibn:ijefaa:v:9:y:2017:i:6:p:124-132
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    References listed on IDEAS

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    1. William F. Sharpe, 1963. "A Simplified Model for Portfolio Analysis," Management Science, INFORMS, vol. 9(2), pages 277-293, January.
    2. Panos Parpas & Berç Rustem, 2007. "Computational Assessment of Nested Benders and Augmented Lagrangian Decomposition for Mean-Variance Multistage Stochastic Problems," INFORMS Journal on Computing, INFORMS, vol. 19(2), pages 239-247, May.
    3. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    4. Steiner, Manfred & Wittkemper, Hans-Georg, 1997. "Portfolio optimization with a neural network implementation of the coherent market hypothesis," European Journal of Operational Research, Elsevier, vol. 100(1), pages 27-40, July.
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    Cited by:

    1. Wang, Yuanrong & Aste, Tomaso, 2023. "Dynamic portfolio optimization with inverse covariance clustering," LSE Research Online Documents on Economics 117701, London School of Economics and Political Science, LSE Library.
    2. Yuanrong Wang & Tomaso Aste, 2021. "Dynamic Portfolio Optimization with Inverse Covariance Clustering," Papers 2112.15499, arXiv.org, revised Jan 2022.

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    More about this item

    Keywords

    portfolio optimization; exchange rates; performance measures; value-at-risk;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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