Skip to main content
Log in

An optimisation approach to constructing an exchange-traded fund

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

In this paper we consider the problem of deciding the portfolio of assets that should underlie an exchange-traded fund (ETF). We formulate this problem as a mixed-integer nonlinear program. We consider ETFs which have positive leverage with respect to their benchmark index and ETFs which have negative leverage (inverse, short, ETFs). Our formulation is a flexible one that incorporates decisions as to both long and short positions in assets, as well as including rebalancing and transaction cost. Computational results are given for problems, derived from universes defined by S&P international equity indices, involving up to 1,200 assets.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Alexander, C., Barbosa, A.: Hedging index exchange traded funds. J. Bank. Finance 32(2), 326–337 (2008)

    Article  Google Scholar 

  2. Avellaneda, M., Zhang, S.: Path-dependence of leveraged ETF returns. SIAM J. Financ. Math. 1(1), 568–603 (2010)

    Article  MathSciNet  Google Scholar 

  3. Beasley, J.E.: Portfolio optimisation: models and solution approaches. In: Topaloglu, H. (Ed) Tutorials in Operations Research, vol. 10, chapter 11, pp. 201–221. INFORMS, Catonsville, Maryland, USA (2013)

  4. Beasley, J.E., Meade, N., Chang, T.-J.: An evolutionary heuristic for the index tracking problem. Eur. J. Oper. Res. 148(3), 621–643 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  5. Boehmer, B., Boehmer, E.: Trading your neighbor’s ETFs: competition or fragmentation? J. Bank. Finance 27(9), 1667–1703 (2003)

    Article  Google Scholar 

  6. Burer, S., Letchford, A.N.: Non-convex mixed-integer nonlinear programming: a survey. Surv. Oper. Res. Manag. Sci. 17(2), 97–106 (2012)

    MathSciNet  Google Scholar 

  7. Bussieck, M.R., Drud, A.S., Meeraus, A.: MINLPLib—a collection of test models for mixed-integer nonlinear programming. Informs J. Comput. 15(1), 114–119 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  8. Bussieck, M.R., Vigerske, S.: MINLP solver software. In: Cochran, J.J., Cox Jr., L.A., Keskinocak, P., Kharoufeh, J.P., Smith, J.C. (Eds.) Wiley Encyclopaedia of Operations Research and Management Science. Wiley, New York (2011). http://www2.mathematik.hu-berlin.de/~stefan/minlpsoft.pdf. Accessed 30 December 2013

  9. Canakgoz, N.A., Beasley, J.E.: Mixed-integer programming approaches for index tracking and enhanced indexation. Eur. J. Oper. Res. 196(1), 384–399 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  10. Chen, C., Kwon, R.H.: Robust portfolio selection for index tracking. Comput. Oper. Res. 39(4), 829–837 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  11. Chiam, S.C., Tan, K.C., Al Mamun, A.: Dynamic index tracking via multi-objective evolutionary algorithm. Appl. Soft Comput. 13(7), 3392–3408 (2013)

    Article  Google Scholar 

  12. Deville, L.: Exchange traded funds: history, trading, and research. In: Zopounidis, C., Doumpos, M., Pardalos, P.M. (Eds.) Handbook of Financial Engineering, Optimization and its Applications, vol. 18, pp. 67–97. Springer, New York (2008)

  13. Garcia, F., Guijarro, F., Moya, I.: The curvature of the tracking frontier: a new criterion for the partial index tracking problem. Math. Comput. Model. 54(7–8), 1781–1784 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  14. Gastineau, G.L.: Exchange-traded funds: an introduction. And further likely evolution. J. Portfol. Manag. 27(3), 88–96 (2001)

    Article  Google Scholar 

  15. Giese, G.: On the risk-return profile of leveraged and inverse ETFs. J. Asset Manag. 11(4), 219–228 (2010)

    Article  Google Scholar 

  16. Guastaroba, G., Speranza, M.G.: Kernel search: an application to the index tracking problem. Eur. J. Oper. Res. 217(1), 54–68 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  17. Haugh, M.B.: A note on constant proportion trading strategies. Oper. Res. Lett. 39(3), 172–179 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  18. Jarrow, R.A.: Understanding the risk of leveraged ETFs. Finance Res. Lett. 7(3), 135–139 (2010)

    Article  Google Scholar 

  19. Kostovetsky, L.: Index mutual funds and exchange-traded funds: a comparison of two methods of passive investment. J. Portfol. Manag. 29(4), 80–92 (2003)

    Article  Google Scholar 

  20. Kupiec, P.H.: A survey of exchange-traded basket instruments. J. Financ. Serv. Res. 4(3), 175–190 (1990)

    Article  Google Scholar 

  21. Leyffer, S., Linderoth, J., Luedtke, J., Mahajan, A., Munson, T.: Minotaur solver. http://wiki.mcs.anl.gov/minotaur/index.php/MINOTAUR. Accessed 30 December 2013 (2013)

  22. Mariani, M.C., Libbin, J.D., Martin, K.J., Ncheuguim, E., Varela, M.P.B., Mani, V.K., Erickson, C.A., Valles-Rosales, D.J.: Levy models and long correlations applied to the study of exchange traded funds. Int. J. Comput. Math. 86(6), 1040–1053 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  23. Meade, N., Beasley, J.E.: Detection of momentum effects using an index out-performance strategy. Quant. Finance 11(2), 313–326 (2011)

    Article  MathSciNet  Google Scholar 

  24. Mezali, H., Beasley, J.E.: Quantile regression for index tracking and enhanced indexation. J. Oper. Res. Soc. 64(11), 1676–1692 (2013)

    Article  Google Scholar 

  25. MINLPLib: http://www.gamsworld.org/minlp/minlplib.htm. Accessed 30 December 2013 (2013)

  26. Mittelmann, H.D.: Performance of commercial and noncommercial optimization software. In: Presented at INFORMS 2012 Phoenix, Arizona. http://plato.asu.edu/talks/phoenix.pdf. Accessed 30 December 2013

  27. Poterba, J.M., Shoven, J.B.: Exchange-traded funds: a new investment option for taxable investors. Am. Econ. Rev. 92(2), 422–427 (2002)

    Article  Google Scholar 

  28. Roman, D., Mitra, G., Zverovich, V.: Enhanced indexation based on second-order stochastic dominance. Eur. J. Oper. Res. 228(1), 273–281 (2013)

    Article  MathSciNet  Google Scholar 

  29. Scozzari, A., Tardella, F., Paterlini, S., Krink, T.: Exact and heuristic approaches for the index tracking problem with UCITS constraints. Ann. Oper. Res. 205(1), 235–250 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  30. Wang, M., Xu, C., Xu, F., Xue, H.: A mixed 0–1 LP for index tracking problem with CVar risk constraints. Ann. Oper. Res. 196(1), 591–609 (2012)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. E. Beasley.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Valle, C.A., Meade, N. & Beasley, J.E. An optimisation approach to constructing an exchange-traded fund. Optim Lett 9, 635–661 (2015). https://doi.org/10.1007/s11590-014-0779-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-014-0779-x

Keywords

Navigation