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Tracking Error: a multistage portfolio model

  • Diana Barro

    (Department of Applied Mathematics - University of Venice)

  • Elio Canestrelli

    (Department of Applied Mathematics - University of Venice)

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.

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File URL: http://128.118.178.162/eps/ge/papers/0510/0510012.pdf
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Paper provided by EconWPA in its series GE, Growth, Math methods with number 0510012.

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Length: 25 pages
Date of creation: 28 Oct 2005
Date of revision:
Handle: RePEc:wpa:wuwpge:0510012
Note: Type of Document - pdf; pages: 25
Contact details of provider: Web page: http://128.118.178.162

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  1. 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.
  2. 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.
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