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Record W4249924096 · doi:10.32920/ryerson.14668107.v1

Dynamic behavior of a nonlinear macro-financial system

2021· preprint· en· W4249924096 on OpenAlexaff
Azadeh Aram

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMacroNonlinear systemHopf bifurcationEconomicsLeverOrder (exchange)Investment (military)Function (biology)ExponentFinancial marketStability (learning theory)BifurcationMathematicsMathematical economicsControl theory (sociology)FinanceComputer sciencePhysics

Abstract

fetched live from OpenAlex

We investigate dynamic behavior of the macro- financial models governed by a system of three first order differential equation involving interest rate, price exponent and investment demand. Using this mathematical model, all the possible behavior that a model shows in the operation of macro-financial system were examined, such as equilibria, stability and Hopf-bifurcations. We find out the ranges of parameters involved in the system under which the equilibria exist the relationship between the parameters and Hopf-bifurcation. Due to changes in conditions in parameters in this financial system, all the behavior of the model as well as the effects of adjustment of the macro-economic policies and adjustment of some parameter on the whole financial system behavior were discussed by applying Ruth-Hurwitz theorem. Hence, It provides better understanding of the lever function of all types of financial policies.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.878
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.221
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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