Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Springer Science and Business Media Deutschland GmbH; 14 October 2020 through 17 October 2020; 14 October 2020 through 17 October 2020
Год издания: 2020
Идентификатор DOI: 10.1007/978-3-030-63319-6_74
Ключевые слова: efficient frontier, investment portfolio, markowitz model, mean-variance analysis, optimal solution
Аннотация: In this paper portfolio optimization problem is studied under premise that the asset classes in investment portfolio are selected but the values of asset returns and variances are random. The sensitivity of the Markowitz model to market uncertainties is described by ‘conservative’, ‘nominal’ and ‘optimistic’ formulations of the problem. An algorithm for defining the initial parameters to describe the conservative and optimistic formulation of the Markowitz problem is developed. The shift of the efficient frontier of portfolios is evaluated. The applicability of the developed model is demonstrated by considering an illustrative example via the Trading Organiser ‘Moscow Exchange’. The nominal, conservative and optimistic portfolio weight distributions are obtained. The difference in the obtained weight distributions and the shift of efficient frontiers confirm that the solution of the Markowitz problem is sensitive to changing market parameters. Mean – standard deviation diagrams for the nominal, optimistic and conservative weight distributions are constructed, the interval values of portfolio means and risk are assessed in real time. It is concluded that portfolios with a conservative weight distribution produce better results than nominal and optimistic portfolios: higher mean return values are obtained at a lower risk. The obtained results are of practical interest under conditions of financial market instability. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
Журнал: Advances in Intelligent Systems and Computing
Выпуск журнала: Vol. 1295
Номера страниц: 797-812
ISSN журнала: 00253159
Информация о публикациях загружается с сайта службы поддержки публикационной активности СФУ. Сообщите, если заметили неточности.