Optimisation of FTSE 100 tracker funds: A comparison of genetic algorithms and quadratic programming Academic Article uri icon

abstract

  • Purpose–Tracker funds offer an attractive balance between risk and return, by providing the profit of the index, with the reduced risk associated with the broad market cover. An effectively designed tracker fund will achieve best tracking of the index with minimal running and trading costs. This paper aims to investigate the use of improved optimisation methods for the design and maintenance of tracker funds. Design/methodology/approach–Most current methods of tracker fund optimisation use quadratic programming (QP), due to its simple formulation and efficient solution. However, the explicit tracking of the return of the index and the optimal selection of the subset of shares composing the fund is not directly available using these methods. This paper investigates ways to overcome the shortcomings of current methods by using genetic algorithms (GA). A GA based tracker fund …

publication date

  • June 1, 2006