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Record W7035835885

Analys av svenska aktie-, ränte- och blandfonders prestationer under perioder av svensk lågkonjunktur

2018· other· sv· W7035835885 on OpenAlexaboutno aff

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2018
Typeother
Languagesv
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentPovertyQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Syftet med denna undersökning är att analysera den riskjusterade avkastningen av svenska aktie-, ränte- och blandfonder under perioder av svensk lågkonjunktur. Undersökningen fokuserar på två perioder av lågkonjunktur, 1996-1999 och 2008-2015, de prestationsmått som används för att analysera de olika fondkategorierna är Sharpekvoten, Treynorkvoten samt Jensens alfa. T-test görs också för att testa skillnaden mellan fondtypernas Sharpe- och Treynorkvoter. Undersökningen visar att räntefonder presterar sämst i termer av riskjusterad avkastning under båda perioderna av lågkonjunktur. Däremot presterar aktiefonderna bäst under första perioden av lågkonjunktur och under den andra perioden presterar blandfonderna bäst. En majoritet av Sharpe- och Treynorkvoterna är statistiskt signifikant skilda mellan de olika fondtyperna.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.003

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 head0.222
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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