A Multi-Step Procedure for Asset Allocation in Case of Limited Resources

Georgieva, Penka; Попчев, Иван; Stoyanov, Stanimir

doi:10.1515/cait-2015-0040

Cited by 15 publications

(9 citation statements)

References 5 publications

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“…price changes. The detailed results in [10,12,13] definitely prove that FSSAM is a reliable tool for detecting future performance of asset prices.…”

Section: Performance Of 4ecmentioning

confidence: 96%

FSSAM: A Fuzzy Rule-Based System for Financial Decision Making in Real-Time

Georgieva¹

2016

Handbook of Fuzzy Sets Comparison - Theory, Algorithms and Applications

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“…price changes. The detailed results in [10,12,13] definitely prove that FSSAM is a reliable tool for detecting future performance of asset prices.…”

Section: Performance Of 4ecmentioning

confidence: 96%

FSSAM: A Fuzzy Rule-Based System for Financial Decision Making in Real-Time

Georgieva¹

2016

Handbook of Fuzzy Sets Comparison - Theory, Algorithms and Applications

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“…, where 𝐸 𝑖 is the mean asset return, estimated according to the historical data 𝑅 𝑖 𝑡 , 𝑖 = 1, … , 𝑁, 𝑡[0, 𝑇] of the return values in period t ∈ [0,T]. The simplest relation between 𝐸 𝑖 and 𝑅 𝑖 𝑡 is given by the average calculation 𝐸 𝑖 = Having the asset characteristics 𝐸 𝑖 , 𝜎 𝑖𝑗 , 𝑖, 𝑗 ∈ [1, 𝑁], the portfolio problem can be modified in the form (5) max 𝐰 [𝐄 T 𝐰 − 𝜆𝐰 T 𝚺𝐰], 𝐰 T |𝟏| = 1, 𝐰 T ≥ 0,…”

Section: Evolution Of the Formal Relations And Variables In The Portfolio Optimization Problemmentioning

confidence: 99%

“…Complication of the portfolio optimization problem has been made by inclusion of additional constraints to the portfolio problem (5). The incorporation of additional constraints allows additional requirements and peculiarities of the portfolio investment process to be tackled.…”

Section: пImentioning

confidence: 99%

The Probabilistic Risk Measure VaR as Constraint in Portfolio Optimization Problem

Stoilov

Stoilova

Vladimirov

2021

Cybernetics and Information Technologies

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The paper realizes inclusion of probabilistic measure for risk, VaR (Value at Risk), into a portfolio optimization problem. The formal analysis of the portfolio problem illustrates the evolution of the portfolio theory in sequentially inclusion of different market characteristics into the problem. They make modifications and complications of the portfolio problem by adding various constraints to consider requirements for taxes, boundaries for assets, cardinality constraints, and allocation of the investment resources. All these characteristics and parameters of the investment participate in the portfolio problem by analytical algebraic relations. The VaR definition of the portfolio risk is formalized in a probabilistic manner. The paper applies approximation of such probabilistic constraint in algebraic form. Geometrical interpretation is given for explaining the influence of the VaR constraint to the portfolio solution. Numerical simulation with data of the Bulgarian Stock Exchange illustrates the influence of the VaR constraint into the portfolio optimization problem.

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“…There are various algorithms for building a fuzzy system. The corresponding type of membership functions (MF) and values of the parameters can be found in [6].…”

Section: Q-measure Fuzzy Logic Module (Qflm)mentioning

confidence: 99%

“…It is a fuzzy rulebased software system, and following the general structure of a fuzzy system, consists of a knowledge base (rule base and database) and an inference machine. [4,5,6,14] Conceptually, fuzzy logic is the basis of Soft Computing (SC) [1,3,9,12,13], enriched with neural networks, evolutionary computing, probabilistic calculations and conclusions [10,11].…”

Section: Introductionmentioning

confidence: 99%