An Investigation into the Noisy Portfolio Optimization Problem

Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

ICMFS02_003

تاریخ نمایه سازی: 23 شهریور 1398

Abstract:

Portfolio optimization is a practical financial application. The task in this problem is to allo-cate capital to a set of assets with the object of maximizing return by minimizing risk. This makes it a multi-objective optimization problem. It is also a noisy problem although, in the literature, noise is of-ten ignored. In classical portfolio optimization, we start with historical returns and use them to con-struct portfolios. Inevitably, the expected returns of the resulting portfolio are noisy. We have no knowledge of future returns. Given the future is an unknown, it can only be estimated, which is affiliat-ed with noise. In this paper Markowitz’s mean-variance portfolio selection model has been used to in-vestigate the impact of noise on the portfolio optimization problem with noisy returns. We demonstrate that investment decisions could be significantly misguided if noise is ignored. Although the results in this paper are negative, the results do have significant implications for investors: they suggest that when returns are noisy, investors should be very cautious about adopting the portfolio optimization results

Authors

Hamid R Jalalian

Faculty of Computer Science, University of Qom, Qom, Iran

Edward Tsang

Academic Member, School of Computer Science and Electrical Engineering, University of Essex, Colchester, Essex, United Kingdom