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The dual approach to portfolio evaluation: a comparison of the static, myopic and generalized buy-and-hold strategies


  • Martin Haugh
  • Ashish Jain


We use the recently proposed duality approach to study the performance of static, myopic and generalized buy-and-hold (GBH) trading strategies. Our interest in static and GBH strategies is motivated by the fact that these strategies are intuitive and straightforward to implement in practice. The myopic strategy, while more difficult to implement, is often close to optimal and so we use it to obtain tight bounds on the performance of the true optimal dynamic trading strategy. We find that while this optimal dynamic strategy often significantly outperforms the GBH strategy, this is not true in general when no-borrowing or no-short-sales constraints are imposed on the investor. This has implications for investors when a dynamic trading strategy is too costly or difficult to implement in practice. For the class of security price dynamics under consideration, we also show that the optimal GBH strategy is always superior to the optimal static strategy. We also demonstrate that the dual approach is even more tractable than originally considered. In particular, we show it is often possible to solve for the theoretically satisfying upper bounds on the optimal value function that were suggested when the dual approach was originally proposed.

Suggested Citation

  • Martin Haugh & Ashish Jain, 2011. "The dual approach to portfolio evaluation: a comparison of the static, myopic and generalized buy-and-hold strategies," Quantitative Finance, Taylor & Francis Journals, vol. 11(1), pages 81-99.
  • Handle: RePEc:taf:quantf:v:11:y:2011:i:1:p:81-99 DOI: 10.1080/14697681003712870

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    References listed on IDEAS

    1. Andersen, Torben G., 1998. "The Econometrics Of Financial Markets," Econometric Theory, Cambridge University Press, vol. 14(05), pages 671-685, October.
    2. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(04), pages 405-426, December.
    3. Campbell, John Y. & Lo, Andrew W. & MacKinlay, A. Craig & Whitelaw, Robert F., 1998. "The Econometrics Of Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(04), pages 559-562, December.
    4. Neely, Christopher J. & Weller, Paul A., 1999. "Technical trading rules in the European Monetary System," Journal of International Money and Finance, Elsevier, vol. 18(3), pages 429-458.
    5. Arjan Berkelaar & Phornchanok Cumperayot & Roy Kouwenberg, 2002. "The Effect of VaR Based Risk Management on Asset Prices and the Volatility Smile," European Financial Management, European Financial Management Association, vol. 8(2), pages 139-164.
    6. Basak, Suleyman & Shapiro, Alexander, 2001. "Value-at-Risk-Based Risk Management: Optimal Policies and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 14(2), pages 371-405.
    7. M. A. H. dempster & C. M. Jones, 2001. "A real-time adaptive trading system using genetic programming," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 397-413.
    8. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    9. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
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    Cited by:

    1. David B. Brown & James E. Smith, 2011. "Dynamic Portfolio Optimization with Transaction Costs: Heuristics and Dual Bounds," Management Science, INFORMS, vol. 57(10), pages 1752-1770, October.
    2. Alonso-GarcĂ­a, J. & Devolder, P., 2016. "Optimal mix between pay-as-you-go and funding for DC pension schemes in an overlapping generations model," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 224-236.


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