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Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms

Andriosopoulos, K., Doumpos, M., Papapostolou, N. C. & Pouliasis, P. K. (2013). Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms. Transportation Research Part E: Logistics and Transportation Review, 52, pp. 16-34. doi: 10.1016/j.tre.2012.11.006

Abstract

This paper reproduces the performance of an international market capitalization shipping stock index and two physical shipping indexes by investing only in US stock portfolios. The index-tracking problem is addressed using the differential evolution algorithm and the genetic algorithm. Portfolios are constructed by a subset of stocks picked from the shipping or the Dow Jones Composite Average indexes. To test the performance of the heuristics, three different trading scenarios are examined: annually, quarterly and monthly rebalancing, accounting for transaction costs where necessary. Competing portfolios are also assessed through predictive ability tests. Overall, the proposed investment strategies carry less risk compared to the tracked benchmark indexes while providing investors the opportunity to efficiently replic ate the performance of both the stock and physical shipping indexes in the most cost-effective way.

Publication Type: Article
Additional Information: © 2012 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: 0102 Applied Mathematics, 0103 Numerical And Computational Mathematics, 1507 Transportation And Freight Services
Departments: Bayes Business School > Finance
SWORD Depositor:
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