A Clustering Application in Portfolio Management
This chapter presents a new asset allocation model which combines a clustering technique with traditional asset allocation methods to improve portfolio Sharpe ratios and portfolio weights stability. The approach identifies optimal clustering patterns in different cluster number cases by using a population-based evolutionary method, namely Differential Evolution. Traditional asset allocations are used to compute the portfolio weights with the clustering. According to the experiment results, it is found that clustering contributes to higher Sharpe ratios and lower portfolio instability than that without clustering. Market practitioners may employ the clustering technique to improve portfolio weights stability and risk-adjusted returns, or for other optimization purposes while distributing the asset weights.
KeywordsClustering optimization asset allocation sharpe ratio weights instability differential evolution
- 5.Gilli, M., Winker, P.: A review of Heuristic optimization methods in econometrics. Working papers, Swiss Finance Institute Research Paper Series, No. 8–12 (2008)Google Scholar
- 6.Harris, R.D.F., Yilmaz, F.: Estimation of the conditional variance – covariance matrix of returns using the intraday range. Working Papers, XFi Centre for Finance and Investment (2007)Google Scholar