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Tracking Error: a multistage portfolio model

Author

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  • Diana Barro

    (Department of Applied Mathematics - University of Venice)

  • Elio Canestrelli

    (Department of Applied Mathematics - University of Venice)

Abstract

We study multistage tracking error problems. Different tracking error measures, commonly used in static models, are discussed as well as some problems which arise when we move from static to dynamic models. We are interested in dynamically replicating a benchmark using only a small subset of assets, considering transaction costs due to rebalancing and introducing a liquidity component in the portfolio. We formulate and solve a multistage tracking error model in a stochastic programming framework. We numerically test our model by dynamically replicating the MSCI Euro index. We consider an increasing number of scenarios and assets and show the superior performance of the dynamically optimized tracking portfolio over static strategies.

Suggested Citation

  • Diana Barro & Elio Canestrelli, 2005. "Tracking Error: a multistage portfolio model," GE, Growth, Math methods 0510012, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:0510012
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    References listed on IDEAS

    as
    1. Ron Dembo & Dan Rosen, 1999. "The practice of portfolio replication. A practical overview of forward and inverse problems," Annals of Operations Research, Springer, vol. 85(0), pages 267-284, January.
    2. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    3. Barro, Diana & Canestrelli, Elio, 2005. "Dynamic portfolio optimization: Time decomposition using the Maximum Principle with a scenario approach," European Journal of Operational Research, Elsevier, vol. 163(1), pages 217-229, May.
    4. Cesari, Riccardo & Cremonini, David, 2003. "Benchmarking, portfolio insurance and technical analysis: a Monte Carlo comparison of dynamic strategies of asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 987-1011, April.
    5. Gaivoronski, Alexei A. & Krylov, Sergiy & van der Wijst, Nico, 2005. "Optimal portfolio selection and dynamic benchmark tracking," European Journal of Operational Research, Elsevier, vol. 163(1), pages 115-131, May.
    6. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    7. Giovanni Barone‐Adesi & Kostas Giannopoulos & Les Vosper, 1999. "VaR without correlations for portfolios of derivative securities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(5), pages 583-602, August.
    8. Bawa, Vijay S., 1978. "Safety-First, Stochastic Dominance, and Optimal Portfolio Choice," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(2), pages 255-271, June.
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    Citations

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    Cited by:

    1. Libo Yin & Liyan Han, 2013. "Options strategies for international portfolios with overall risk management via multi-stage stochastic programming," Annals of Operations Research, Springer, vol. 206(1), pages 557-576, July.
    2. Diana Barro & Elio Canestrelli, 2008. "Tracking error with minimum guarantee constraints," Working Papers 172, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    3. Diana Barro & Elio Canestrelli, 2014. "Downside risk in multiperiod tracking error models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 263-283, June.
    4. Diana Barro & Elio Canestrelli, 2012. "Dynamic tracking error with shortfall control using stochastic programming," Working Papers 2012_18, Department of Economics, University of Venice "Ca' Foscari", revised 2012.
    5. Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2012. "Exact and Heuristic Approaches for the Index Tracking Problem with UCITS Constraints," Department of Economics 0685, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    6. Aleksandr G. Alekseev & Mikhail V. Sokolov, 2016. "Benchmark-based evaluation of portfolio performance: a characterization," Annals of Finance, Springer, vol. 12(3), pages 409-440, December.
    7. Diana Barro & Elio Canestrelli, 2005. "Time and nodal decomposition with implicit non-anticipativity constraints in dynamic portfolio optimization," GE, Growth, Math methods 0510011, University Library of Munich, Germany.
    8. Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2013. "Exact and heuristic approaches for the index tracking problem with UCITS constraints," Annals of Operations Research, Springer, vol. 205(1), pages 235-250, May.
    9. Aleksandr Alekseev & Mikhail Sokolov, 2016. "Portfolio Return Relative to a Benchmark," EUSP Department of Economics Working Paper Series 2016/04, European University at St. Petersburg, Department of Economics.
    10. Diana Barro & Elio Canestrelli, 2011. "Combining stochastic programming and optimal control to solve multistage stochastic optimization problems," Working Papers 2011_24, Department of Economics, University of Venice "Ca' Foscari", revised 2011.
    11. Alexander Alekseev & Mikhail Sokolov, 2016. "Portfolio Return Relative to a Benchmark," EUSP Department of Economics Working Paper Series Ec-04/16, European University at St. Petersburg, Department of Economics.
    12. Diana Barro & Elio Canestrelli & Giorgio Consigli, 2019. "Volatility versus downside risk: performance protection in dynamic portfolio strategies," Computational Management Science, Springer, vol. 16(3), pages 433-479, July.
    13. Emilio Ricardo Carvalhais & Antonio Marcos Duarte Júnior, 2015. "Indexation of Fixed-Income Portfolios to the IMA-B," Brazilian Business Review, Fucape Business School, vol. 12(3), pages 116-142, May.
    14. Jun Nakayama & Daisuke Yokouchi, 2018. "Applying Time Series Decomposition to Construct Index-Tracking Portfolio," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(4), pages 341-352, December.
    15. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    16. Leonardo Riegel Sant’Anna & Tiago Pascoal Filomena & Pablo Cristini Guedes & Denis Borenstein, 2017. "Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming," Annals of Operations Research, Springer, vol. 258(2), pages 849-867, November.
    17. Diana Barro & Elio Canestrelli, 2016. "Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 711-742, July.

    More about this item

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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