Development of an efficient cluster-based portfolio optimization model under realistic market conditions
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Development of an efficient cluster‑based portfolio optimization model under realistic market conditions Mahdi Massahi1 · Masoud Mahootchi1 · Alireza Arshadi Khamseh2 Received: 30 August 2016 / Accepted: 29 July 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Modern portfolio theory introduced by Markowitz in 1952 is the most popular portfolio optimization framework established based on the trade-off between risk and return as an operation research model. The main shortcoming of applying Markowitz portfolio optimization in practice is that the obtained optimal weights are really sensitive to the embedded uncertainty in return series of stocks. In this paper, it is demonstrated how using a new methodology of time series clustering as a remedy can lead to a more robust and accurate portfolio in terms of the gap between mean variance efficient frontier obtained from the optimization model and the one observed in reality. In this regard, two similarity measures, the autocorrelation coefficients and the weighted dynamic time warping, are used in an innovative way to construct the desired portfolio optimization model. Moreover, the effectiveness of proposed approach is investigated in two different market conditions: semi-realistic and full-realistic. In the first one, it is assumed that the forecasted and realized stocks mean returns are the same; however, these returns are not necessarily equal in the second market conditions. Finally, a database of stock prices from the literature is utilized to show the robustness and accuracy of the proposed approach in empirical results in comparison with applied similarity measures in previous researches. Keywords Portfolio optimization · Realized efficient frontier · Time series clustering · Weighted dynamic time warping · Autocorrelation coefficient · Realistic market condition * Masoud Mahootchi [email protected]; [email protected] Mahdi Massahi [email protected] Alireza Arshadi Khamseh [email protected] 1
Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, 424 Hafez Ave., Tehran, Iran
2
Department of Industrial Engineering, Kharazmi University, 43 Shahid Mofateh Ave., Tehran, Iran
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Vol.:(0123456789)
M. Massahi et al.
JEL Classification G11 · C61 · C63 · C38
1 Introduction Nowadays, portfolio management and finding an optimal portfolio are common issues in finance. The modern portfolio theory was firstly reviewed in the work of Markowitz (1959) and Sharpe (1964) who were awarded the Nobel Prize in Economics in 1990. Since 1990, many authors have investigated how to find the optimal portfolio and a wide range of methods for portfolio selection and optimization have been used (see, for example, Ehrgott et al. 2004; Lin and Liu 2008; Best 2010; Vaclavik and Jablonsky 2012; Cong and Oosterlee 2016). Financial experts believe that diversification of investment is vital to create an efficient portfolio. Tola et al. (2008) indicated that, to make a diversified portfolio, clustering ap
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