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Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context

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In this paper, we present an analysis of the effectiveness of various portfolio optimization strategies applied to the stocks included in the Spanish Ibex 35 index, for a period of 14 years, from 2001 until 2014. The period under study includes episodes of volatility and instability in financial markets, incorporating the Global Financial Crisis and the European Sovereign Debt Crisis. This implies a challenge in portfolio optimization strategies since the methodologies are restricted to the assignment of positive weights. We have taken for asset allocation the daily returns with an estimation window equal to 1 year and we hold portfolio assets for another year. We evaluate the out-of-sample performance of 15 strategies for asset allocation in the Ibex 35 index, before and after of the Global Financial Crisis. Our results suggest that a large number of strategies outperform to the 1/N rule and to the Ibex 35 index in terms of return, Sharpe ratio and lower VaR and CVaR. The mean-variance portfolio of Markowitz with shortsale constraints, it is the only strategy that renders a Sharpe ratio statistically different to Ibex 35 index in the 2001-2007 and 2008-2014 periods.

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  • Víctor M. Adame-García & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, "undated". "Portfolios in the Ibex 35 index: Alternative methods to the traditional framework, a comparative with the naive diversification in a pre- and post- crisis context," Documentos de Trabajo del ICAE 2015-07, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Jun 2015.
  • Handle: RePEc:ucm:doicae:1507
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    More about this item

    Keywords

    Portfolio optimization; Portfolio diversification; Markowitz Analysis; Naive 1/N strategy; Ibex35.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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