Open AccessComplete Neighbourhood Search Heuristic Algorithm for Portfolio Optimization
Author(s) -
Collether John
Publication year - 2022
Publication title -
tanzania journal of engineering and technology/tanzania journal of engeering and technology
Language(s) - English
Resource type - Journals
eISSN - 1821-536X
pISSN - 2619-8789
DOI - 10.52339/tjet.v40i2.736
Subject(s) - mathematical optimization , portfolio optimization , computer science , optimization problem , quadratic programming , cardinality (data modeling) , maxima and minima , heuristic , portfolio , algorithm , mathematics , economics , mathematical analysis , financial economics , data mining
In portfolio optimization, the fundamental goal of an investor is to optimally allocate investments between different assets. Mean-variance optimization methods make unrealistic assumptions to solve the problem of optimal allocation. On the other hand, when realistic constraints like holding size and cardinality are introduced it leads to optimal asset allocation which differ from the mean variance optimization. The resulting optimization problem become quite complex as it exhibits multiple local extrema and discontinuities. Heuristic algorithms work well for the complex problem. Therefore, a heuristic algorithm is developed which is based on hill climbing complete (HC-C). It is utilized to solve the extended portfolio optimization problem. In order to validate its performance, the proposed HC-C is tested with standard portfolio optimization problem. Experimental results are benchmarked with the quadratic programming method and threshold accepting (TA) algorithm.