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Record W7029095223

Integrierte Modellierung von Zins- und Aktienmärkten

2011· article· de· W7029095223 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenuemediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 2011
Typearticle
Languagede
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsnot available
Fundersnot available
KeywordsInflation (cosmology)Kalman filter
DOInot available

Abstract

fetched live from OpenAlex

Im Rahmen dieser Diplomarbeit wurde ein kaskadenartig aufgebautes Modell zur Beschreibung von Inflations- und Zinsraten sowie von Aktienrenditen auf dem amerikanischen Finanzmarkt entwickelt. In einem ersten Schritt wurden das reale Wirtschaftswachstum und die Inflation (in Form einer short inflation) mittels stochastischer Differentialgleichungen modelliert und die entspre-chenden Parameter geschätzt. Darauf aufbauend wurde ein Modell für die realen Zinsen mit dem Wirtschaftwachstum als zusätzlichem Faktor entwickelt. Alle genannten Faktoren waren dann Einflussgrößen für das Modell der stetigen Aktien-marktrenditen. Die Schätzungen wurde mit Hilfe des Kalman Filters durchgeführt. Alle Modelle wurden umfassend analysiert und bzgl. der geforderten Annahmen überprüft. Als Vergleichsmodelle dienten die Finanzmarktmodelle von Barrie und Hibbert.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.008
Scholarly communication0.0000.001
Open science0.0070.006
Research integrity0.0010.003
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 head0.051
GPT teacher head0.253
Teacher spread0.202 · 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