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Record W3004121352

2010-03: Australian Art Market Prices during the Global Financial Crisis and two earlier decades (Working paper)

2010· article· en· W3004121352 on OpenAlexaboutno aff
Helen Higgs

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Financial crisisDiversification (marketing strategy)PortfolioEconomicsIndex (typography)PaintingFinancial economicsHedonic regressionPrice indexBusinessEconometricsGeographyArtArt historyMacroeconomicsMarketing
DOInot available

Abstract

fetched live from OpenAlex

This study constructs a quarterly hedonic price index using 64,203 artworks, by seventyone\nwell-known modern and contemporary Australian artists, sold at auction houses over the period 1986-2009. The hedonic regression model includes characteristics such as name and living status of the artist, the size and medium of the painting, and the auction house, quarter and year in which the painting was sold. The resulting index indicates that returns on Australian fine-art averaged one percent in nominal terms over the period from quarter one 1986 to quarter four 2009 with a standard deviation of seventeen percent. During the global financial crisis spanning quarter one 2008 and quarter four 2009, the average art returns declined in nominal terms by close to six percent with a standard deviation of twenty-one percent. This study also shows that over the entire period the art market only marginally underperformed the stock and housing markets. The low correlations between these markets suggest the benefits of portfolio diversification.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.311
Teacher spread0.245 · 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 designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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