Experton approach to vague information in portfolio selection problem with many views

Rutkowska, Aleksandra; Bartkowiak, Marcin

doi:10.2991/eusflat-19.2019.22

Cited by 4 publications

(4 citation statements)

References 26 publications

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“…Враховуючи, що дохідність наявних в портфелі активів носить стохастичний характер, інвестори допускають його оптимізацію із додаванням певних обмежень щодо категорій активів і розділень періодів інвестування, як запропоновано X. Huang i X. Wang, (Huang & Wang, 2019) а також E. Allaj (Allaj, 2020). В роботах A. Palczewski і J. Palczewski (Palczewski & Palczewski, 2019), а також A. Rutkowska і M. Bartkowiak (Rutkowska & Bartkowiak, 2019) запропонована оптимізація наповнення портфеля, що додатково потребує відповідних аналітичних досліджень від експертів, які інколи приводять до значних розбіжностей в намірах щодо кінцевого результату, як продемонстровано F. Wen, L. Xu, G. Ouyang і G. Kou в (Wen et al, 2019). Відповідно розв'язання портфельних проблем, пов'язаних зі зниженням інвестиційних ризиків, що є більш прийнятно для інвесторів, виконується за допомогою кількісної оцінки ризику шляхом прийняття багатокритеріальних рішень і кластеризації, що обґрунтовано G. Kou, Ö. Akdeniz, H. Dinçer і S. Yüksel (Kou et al, 2021).…”

Section: вступunclassified

Information system of analysis for segmentation of the securities portfolio of the product market

Stepanyuk,

Senyk,

Manziy

et al. 2023

SMLNUVMBE

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The investment market is a complex competitive environment where speed and accuracy of decision-making play a crucial role. Understanding sentiment and asset behavior is key to forecasting and successful investment portfolio management. The results of information analysis confirm the hypothesis of the effectiveness of food market assets, and this in turn proves the possibility of increasing the portfolio's profitability by including food sector assets in it. Creation of an information analysis system for the purpose of segmentation of the contained portfolio is an urgent task, which will allow obtaining real and objective information about the potential risk and profitability of various assets. The paper provides an overview of specialized applied software products that are available on the Internet and are used to analyze financial data. An overview of modern information technologies, which allow convenient processing, visualization of data and forecasting of asset price movements, was carried out. An alternative version of the own information system of analysis is proposed, which focuses on the assets of the food sector. The main task of the created information system is to provide convenient tools for market data analysis, visualization and forecasting of price movements. The main functionalities of the created system are described, including a visual comparison of historical data, price movement forecasting using machine learning, and recommendations on the optimal content of the investment portfolio. The conducted example of the analysis demonstrates how the received information will help to reduce risks and increase the efficiency of decision-making, when managing a portfolio that contains assets of the food sector. The results of the work show that in the case of a small set of assets and, accordingly, restrictions on the diversification of capital investments, the use of such information systems in the field of food products is effective and profitable. The presented technique also demonstrates that an investor, even with non-professional knowledge in the field of programming and information and communication technologies, can effectively use them to create specialized systems for data analysis, visualization and forecasting.

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Section: вступunclassified

Information system of analysis for segmentation of the securities portfolio of the product market

Stepanyuk,

Senyk,

Manziy

et al. 2023

SMLNUVMBE

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“…They focused on a fuzzy compromise programming to find a solution of fuzzy return maximization and fuzzy beta minimization. This method was followed by studies, where views were assumed to be fuzzy random numbers [16,17]. Both studies include investor opinion using fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

“…Experton theory was developed by Kaufman [19] and is already applied in many fields. They seem to be particularly widely applicable in economic and other sciences to diagnose the financial conditions of company [20], to model mental workload [21], for use in decision and multi-decision problems [22,23], to predict prices in the agro-food sector [24], for SWOT analysis [25] and to optimize investment [17,26].…”

Section: Introductionmentioning

confidence: 99%

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Vague Expert Information/Recommendation in Portfolio Optimization-An Empirical Study

Bartkowiak

Rutkowska

2020

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In a real market, the quantity of information and recommendations is constantly increasing. However, recommendations are often in linguistic form and no one recommendation is based on a single piece of information. Predictions of individuals and their confidence can vary greatly. Thus, a problem arises concerning different (disjointed or partially coherent) vague opinions of various experts or information from multiple sources. In this paper, we introduce extensions of the Black—Litterman model with linguistic expressed views from different experts/many sources. The study focuses on empirical analysis of proposed fuzzy approach results. In the presented modification every expert presents its opinion about particular assets according to intervals, and then an experton for each asset is built. In the portfolio optimization, we use aggregated views presented by interval, which is the mean value of the experton built on particular views. In an empirical study, we built and tested 10,000 portfolios based on recommendation from EquityRT, which was made by 14–49 experts monthly between November 2017 and June 2019 for the 29 biggest companies from the US market and different sectors. The annual average return from portfolios is 9.5–11.8%, depending on the width of the intervals and additional constraints. This approach allows people to formulate intuitive views and view the opinions of a group of experts.

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Decision Support for Portfolio Management by Information System with Black–Litterman Model

Stoilov

Stoilova

Vladimirov

2021

Int. J. Info. Tech. Dec. Mak.

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An algorithm is derived for the development of portfolio decision-support information service. The algorithm allows being automated evaluations for the definition and solution of portfolio problems. Small set of historical data of asset returns with limited set of assets are used for the portfolio, which is the case for no institutional portfolio manager. The algorithm applies analytical relations for decreasing the computational workload for the estimation of the market parameters due to the limited number of assets. The subjective expert views in the Black–Litterman (BL) model are defined from additional assessment of historical data of the asset returns. The algorithm makes comparisons of the results for active portfolio management from the mean variance (MV) model, the BL one and the equal-weighted investment strategy. Benefits of the algorithm are the usage of small set of historical data and limited number of assets, which are proved in investment rolling horizon.

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Experton approach to vague information in portfolio selection problem with many views

Cited by 4 publications

References 26 publications

Information system of analysis for segmentation of the securities portfolio of the product market

Information system of analysis for segmentation of the securities portfolio of the product market

Vague Expert Information/Recommendation in Portfolio Optimization-An Empirical Study

Decision Support for Portfolio Management by Information System with Black–Litterman Model

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