Asset allocation with correlation: A composite trade-off
Thomas Conlon (),
John Cotter () and
European Journal of Operational Research, 2017, vol. 262, issue 3, 1164-1180
We assess the ability of minimum-variance portfolio allocation strategies accounting for time-varying correlation between assets to provide performance benefits relative to an equally-weighted portfolio. Prior to transaction costs correlation-based strategies emphatically outperform the equally-weighted benchmark. This finding is strongest for short horizon correlation forecasts and attributed to dynamic correlation as opposed to variance forecasts. Thus, estimation error is not found to be the primary obstacle to successful portfolio optimization. Rather, frequent rebalancing and associated transaction costs pose a significant challenge. Limiting portfolio turnover through short-selling restrictions and greater rebalancing error tolerance results in regular outperformance of the correlation based strategies even for large transaction costs. Taken together, these findings provide evidence of a trade-off between optimal portfolio performance, forecasting horizon, rebalancing frequency and transaction costs.
Keywords: Decision analysis; Optimization; Asset allocation; Dynamic correlation; Rebalancing and transaction costs (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:262:y:2017:i:3:p:1164-1180
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().