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Modeling an Indexed Portfolio for the Italian Market


  • Rita L.D'Ecclesia, Marida Bertocchi, Jozsef Abaffy


Portfolio manager's performance is often evaluated respect to a predetermined market benchmark. Usually the benchmark is an equity/bond portfolio or index for which the percentage and the bond duration are specified, so the manager's aim is to build a portfolio whose performance replicates the benchmark performance. To achieve returns equal or higher than the market benchmark the development of indexation strategies for managing assets allocation has been required. In this paper we consider the problem of a portfolio manager aiming to manage a fixed-income portfolio in a way that it tracks a broadly defined market index. To track a fixed-income index is a complex task since these indices are built in order to reflect the overall market so their composition is determined without considering liquidity constraints or diversification aspects.In addition the rebalancing of a fixed-income index does not require additional transaction costs. On the other hand, an asset manager when building a fixed income portfolio has to guarantee a certain diversification with only few securities. He deals with transaction costs and faces the problem of the cash flows generated by the bonds that cannot be reinvested in the same security but usually are invested in the money markets. In case of fixed income portfolios we deal with securities with a finite life whose rate of returns vary as they approach maturity. For these securities historical data are of limited value, in addition the assumption of symmetric distribution for the returns does not hold so the traditional mean-variance approach may not be adopted for portfolio selection. In this paper, following the approach used by Zenios, we use integrated simulation and optimization models for tracking a fixed income index for the Italian Market.

Suggested Citation

  • Rita L.D'Ecclesia, Marida Bertocchi, Jozsef Abaffy, 2001. "Modeling an Indexed Portfolio for the Italian Market," Computing in Economics and Finance 2001 28, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:28

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    More about this item


    scenario simulation; non linear optimization; indexed portfolio.;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications


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