Winnowing algorithm with enhanced exploration to optimise portfolio weights. (26th August 2020)

• Record Type: Journal Article
• Authors: Chawda, Bharat V.; Patel, Jayeshkumar M.
• Is Part Of: International journal of intelligent information and database systems. Volume 13:Number 2/4(2020)
• Page Start: 411
• Page End: 435
• Publication Date: 2020-08-26
• Subjects: winnowing algorithm -- enhanced exploration -- natural computing -- nature inspired algorithm -- portfolio management -- weight optimisation; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

The winnowing algorithm is a newly introduced natural computing algorithm. It is inspired by the real world winnowing process which is a separation process used to separate heavier and lighter components from the mixture by the help of wind. The winnowing algorithm has been found accurate, robust and effective in the comparative analysis of experimental results with other state-of-the-art natural computing algorithms. Similar to other natural computing algorithms, the winnowing algorithm also attempts to explore search space as broadly as possible along with exploiting generated solutions to obtain optimal solution iteration by iteration. This paper presents an enhanced approach for the exploration of the search space to further improve the performance of this algorithm. The performance of the algorithm has been tested on the standard dataset of five assets to optimise portfolio weights. Obtained results show significant improvement in the performance of the algorithm.