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Record W1876725434 · doi:10.5539/ijsp.v4n3p150

A Note on $\mathbb{L}_{2}$-structure of Continuous-time Bilinear Processes with Time-varying Coefficients

2015· article· en· W1876725434 on OpenAlexvenueno aff
Abdelouahab Bibi, Fateh Merahi

Bibliographic record

VenueInternational Journal of Statistics and Probability · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Risk and Volatility Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsCovarianceBilinear interpolationApplied mathematicsTerm (time)Brownian motionOrder (exchange)Probabilistic logicGaussianCovariance functionStatistics

Abstract

fetched live from OpenAlex

This paper is concerned with the investigation of $\mathbb{L}_{2}$-structureissue of time-varying coefficients continuous-time bilinear processes ($COBL$)driven by a Brownian motion $\left(BM\right)$. Such processes are veryuseful for modeling irregular spacing non linear and non Gaussian datasets andmay be proposed to model for instance some financial returns representing highamplitude oscillations and thus make it a serious candidate for describeprocesses with time-varying degree of persistence and other complex systems.Our attention is focused however on the probabilistic structure of $COBL$processes, so, we establish necessary and sufficient conditions for theexistence of regular solutions in term of their transfer function. Expliciteformulas for the mean and covariance functions are given. As a consequence, weobserve that the second order structure is similar to a $CARMA$ processes withsome uncorrelated noise. Therefore, it is necessary to look intohigher-order cumulant in order to distinguish between $COBL$ and $CARMA$ processes.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.592
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.023
GPT teacher head0.250
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

Classification

machine, unvalidated

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

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2015
Admission routes1
Has abstractyes

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