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Record W3081900971 · doi:10.3390/jrfm13090195

Portfolio Theory in Solving the Problem Structural Choice

2020· article· en· W3081900971 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of risk and financial management · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsPortfolioPortfolio optimizationModern portfolio theoryPost-modern portfolio theoryEfficient frontierBlack–Litterman modelComputer scienceRate of return on a portfolioReplicating portfolioApplication portfolio managementSeparation propertyMerton's portfolio problemEconomicsMathematical optimizationEconometricsMathematical economicsMathematicsProject portfolio managementFinancial economics

Abstract

fetched live from OpenAlex

The purpose of the article is to reveal the problem (and to determine the possibility of solving the structural choice problem) as one of the areas in modern portfolio theory development. The article also argues that portfolio analysis is a method of structural analysis for various economic units. The research methodology is defined by the portfolio theory, optimization models implemented by the numerical gradient projection method, the empirical static method of analysis and simulation cases when the models are implemented. The research supported by the above- mentioned methodology aimed to reach the goal results in substantiating the structural choice. This choice differs from the classical portfolio choice as it is necessary to find how the investments are allocated for the portfolio units, and the same should be done for the characteristics points, where it is a challenge to apply the efficient set theorem, because different structures for the allocation of the resources, investments give the same or nearly the same combination of the expected return and total portfolio risk. Economic sectors characterized by the profitability and business risk are seen to be the portfolio units in terms of the macroeconomic approach from the portfolio theory developed by Tobin. Total income maximization model and total portfolio risk minimization demonstrate both the structural choice problem, including at the characteristic points, and choice dependence on the expansion of the resource allocated to the portfolio, and on the number of portfolio units. The analysis and model simulations enhance the efficient set theorem with the criteria for structural choice—income and risk correlation on the effective distribution curve, among other factors. A portfolio with two real sectors of the Russian economy illustrates that profitability and risk ratio determines the resource allocation between them under the income maximization model, so one sector grabs a more substantial resource. Thus, being a tool to support the structural choice, portfolio analysis gives structural diagnostics for the resource distribution, investments allocation by portfolio units.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.240
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it