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ИД «Финансы и кредит»






Financial Analytics: Science and Experience

Ranking framework for portfolio selection

Vol. 15, Iss. 3, SEPTEMBER 2022

Received: 3 September 2019

Received in revised form: 16 September 2019

Accepted: 30 September 2019

Available online: 30 August 2022


JEL Classification: C58, G23

Pages: 354–372


Dmitrii G. LEVSHUK Polotsk State University (PSU), Novopolotsk, Vitebsk Oblast, Republic of Belarus


Subject. The stock market is characterized by a significant variety of economic processes. Classical methods for modeling the time series to analyze and forecast processes in the stock market often produce unsatisfactory results. The article investigates and encourages new approaches to projections in the stock market in the face of uncertainty.
Objectives. The aim is to develop a technique to examine rank decisions in portfolio analysis.
Methods. In the research process, I used data analysis and machine learning methods.
Results. I examined the procedure for ranking portfolio solutions. This procedure rests on replacing optimization with a preference analysis commonly used in expert data processing. The replacement is possible due to the use of a special equation that includes the probability of positive yield as a factor.
Conclusions. I suggest using probabilistic preference technique based on the auto predictive model, instead of optimization approach to portfolio selection. The main result of this technique is rank portfolio formation that expands opportunities of portfolio analysis.

Keywords: probability, portfolio, binary choice


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