Skip to main content
Log in

Tailor-made thematic portfolios: a core satellite optimization

  • Published:
Journal of Global Optimization Aims and scope Submit manuscript

Abstract

In recent years, thematic exchange-traded funds have arisen and broaden the narrow thinking of purely monetary driven investment decisions. Ethical concerns, a stronger belief in society-shaped trends, or the conformity with personal convictions motivate investors to include non-monetary objectives in so called thematic funds. Thematic investors follow a modified core satellite strategy in which conventional funds ensure diversification. Investors’ non-monetary interests manifest within additional satellite funds. Both portfolios are separately allocated so that inter-portfolio correlation effects are not considered and inefficient core satellite portfolios are allocated. However, in order to reduce the inefficiency of such a core satellite strategy, this study addresses fund providers and develops the idea of tailoring thematic funds to conventional ones. An empirical investigation shows that by easing the efficiency constraint for the satellite portfolio, correlation effects between the portfolios can be exploited. At the expense of an average relative volatility increase of 4.55%, the inefficiency of core satellite portfolios can be reduced by an average of 11.74% compared to volatilities of efficient tri-criterion portfolios. Further analysis of these thematic products shows that tailored products can also be more concentrated within a given theme. This opens up new opportunities for fund providers to become more involved in various thematic trends and at the same time achieve better performance for core satellite investors.

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

Notes

  1. This is only a notation for simplicity in line with several studies and is not be understood as quasi code [13, 16, 23].

References

  1. Markowitz, H.: Portfolio selection. J. Finance (1952). https://doi.org/10.2307/2975974

    Article  Google Scholar 

  2. Anand, P., Cowton, C.J.: The ethical investor. Exploring dimensions of investment behaviour. J. Econ. Psychol. (1993). https://doi.org/10.1016/0167-4870(93)90007-8

    Article  Google Scholar 

  3. Marchioni, U., Antropova, S., Thomson, C., McNaught, C., Schwaiger, K.: Megatrends. An index approach to thematic investing (2016). https://www.ishares.com/uk/individual/en/literature/brochure/ishares-megatrends-thematic-investing-en-gb-rc-end-investor.pdf. Accessed 14 Nov 2017

  4. Giammattei, G.: Global Megatrends: Capitalizing on Tomorrow’s Trends Today. RBC Global Asset Management (U.S.) Inc., Boston (2014)

    Google Scholar 

  5. Sironi, P.: FinTech Innovation. From Robo-advisors to Goal Based Investing and Gamification. Wiley Finance Series. Wiley, Chichester (2016)

    Book  Google Scholar 

  6. Zopounidis, C., Niklis, D., Doumpos, M.: Doumpos, M.: “Financial decision support”. Feature issue editorial. EURO J. Decis. Process. (2018). https://doi.org/10.1007/s40070-018-0080-9

    Article  Google Scholar 

  7. Bérubé, V., Ghai, S., Tétrault, J.: From indexes to insights: the rise of thematic investing. McKinsey Invest. Winter 2014/15(1), 51–56 (2014)

    Google Scholar 

  8. Forster, G.: On theme. Superfunds Mag. 424, 16 (2017)

    Google Scholar 

  9. Methling, F., Nitzsch, R. von: Thematic portfolio optimization—challenging the core satellite approach (2018). https://doi.org/10.2139/ssrn.3227775

  10. Aouni, B., Doumpos, M., Pérez-Gladish, B., Steuer, R.E.: On the increasing importance of multiple criteria decision aid methods for portfolio selection. J. Oper. Res. Soc. (2018). https://doi.org/10.1080/01605682.2018.1475118

    Article  Google Scholar 

  11. Steuer, R.E., Qi, Y., Hirschberger, M.: Multiple objectives in portfolio selection. J. Financ. Dec. Mak. 1(1), 5–20 (2005)

    MATH  Google Scholar 

  12. Steuer, R.E., Qi, Y., Hirschberger, M.: Portfolio selection in the presence of multiple criteria. In: Handbook of Financial Engineering (2008). https://doi.org/10.1007/978-0-387-76682-9_1

    Chapter  Google Scholar 

  13. Steuer, R.E., Qi, Y., Hirschberger, M.: Suitable-portfolio investors, nondominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection. Ann. Oper. Res. (2007). https://doi.org/10.1007/s10479-006-0137-1

    Article  MathSciNet  MATH  Google Scholar 

  14. Ballestero, E., Bravo, M., Pérez-Gladish, B., Arenas-Parra, M., Plà-Santamaria, D.: Socially responsible investment. A multicriteria approach to portfolio selection combining ethical and financial objectives. Eur. J. Oper. Res. 25, 55 (2012). https://doi.org/10.1016/j.ejor.2011.07.011

    Article  MathSciNet  Google Scholar 

  15. Zopounidis, C., Doumpos, M.: Multiple Criteria Decision Making. Springer, Cham (2017)

    Book  Google Scholar 

  16. Hirschberger, M., Steuer, R.E., Utz, S., Wimmer, M., Qi, Y.: Computing the nondominated surface in tri-criterion portfolio selection. Oper. Res. (2013). https://doi.org/10.1287/opre.1120.1140

    Article  MathSciNet  MATH  Google Scholar 

  17. Gasser, S.M., Rammerstorfer, M., Weinmayer, K.: Markowitz revisited Social portfolio engineering. Eur. J. Oper. Res. (2017). https://doi.org/10.1016/j.ejor.2016.10.043

    Article  MathSciNet  MATH  Google Scholar 

  18. Amenc, N., Malaise, P., Martellini, L.: Revisiting core-satellite investing. Portf. Manag. (2004). https://doi.org/10.3905/jpm.2004.443322

    Article  Google Scholar 

  19. Magoon, C.: Better than sectors. The case for thematic investing. J. Indexes 12(5), 18–25 (2009)

    Google Scholar 

  20. Brough, M., Shepperson, A.: International Pension Plan Survey Report 2018. Willis Towers Watson (2019)

  21. Zopounidis, C., Galariotis, E., Doumpos, M., Sarri, S., Andriosopoulos, K.: Multiple criteria decision aiding for finance. An updated bibliographic survey. Eur. J. Oper. Res. (2015). https://doi.org/10.1016/j.ejor.2015.05.032

    Article  MathSciNet  MATH  Google Scholar 

  22. Markowitz, H.: Portfolio Selection. Efficient Diversification of Investments, 2nd edn. Blackwell, Cambridge, MA (1996)

    Google Scholar 

  23. Ehrgott, M., Klamroth, K., Schwehm, C.: An MCDM approach to portfolio optimization. Eur. J. Oper. Res. (2004). https://doi.org/10.1016/s0377-2217(02)00881-0

    Article  MathSciNet  MATH  Google Scholar 

  24. Utz, S., Wimmer, M., Steuer, R.E.: Tri-criterion modeling for constructing more-sustainable mutual funds. Eur. J. Oper. Res. (2015). https://doi.org/10.1016/j.ejor.2015.04.035

    Article  MathSciNet  MATH  Google Scholar 

  25. Evans, J.L., Archer, S.H.: Diversification and the reduction of dispersion. An empirical analysis. J. Finance (1968). https://doi.org/10.1111/j.1540-6261.1968.tb00315.x

    Article  Google Scholar 

  26. Statman, M.: How many stocks make a diversified portfolio? J. Financ. Quant. Anal. (1987). https://doi.org/10.2307/2330969

    Article  Google Scholar 

  27. Tang, G.Y.: How efficient is naive portfolio diversification? An educational note. Omega (2004). https://doi.org/10.1016/j.omega.2003.10.002

    Article  Google Scholar 

  28. MSCI: GICS Structure. Effective Sep1, 2016. https://www.msci.com/documents/10199/4547797/GICS+Structure+effective+Sep+1%2C+2016.xls/d8600f87-cc12-4070-912f-08590232441d (2016). Accessed 22 Dec 2017

  29. Sharpe, W.F.: Mutual fund performance. J. Bus. 39(1), 119–138 (1966)

    Article  Google Scholar 

  30. Woerheide, W., Persson, D.: An index of portfolio diversification. Financ. Serv. Rev. 2(2), 73–85 (1993)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Florian Methling.

Ethics declarations

Conflict of interest

None.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Simulation histograms

Appendix: Simulation histograms

figure a

Histograms show the results of the simulation with 3826 assets and a random evaluation of thematic assets for different amounts of conventional assets nC. Within the histograms, the different lines show each 1000 results concerning different amounts of thematic assets. Histogram “All” summarizes the 25,000 results of the five previous histograms.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Methling, F., von Nitzsch, R. Tailor-made thematic portfolios: a core satellite optimization. J Glob Optim 76, 317–331 (2020). https://doi.org/10.1007/s10898-019-00781-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10898-019-00781-2

Keywords

Navigation