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Record W2364699575 · doi:10.1093/rof/rfv042

Investors’ Interacting Demand and Supply Curves for Common Stocks

2015· article· en· W2364699575 on OpenAlexaff
Martin Dierker, Jung-Wook Kim, Jason Lee, Randall Mørck

Bibliographic record

VenueEuropean Finance Review · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of Alberta
FundersInstitute of Management Research, College of Business Administration Seoul National University
KeywordsEconomicsSupply and demandStock (firearms)Financial crisisStock marketEconometricsMonetary economicsOrder (exchange)Financial economicsMicroeconomicsMacroeconomicsFinance

Abstract

fetched live from OpenAlex

Abstract Complete limit order data from Korea show individual stocks’ demand and supply elasticities correlating negatively in short windows. That is, whenever a stock’s demand is unusually elastic, its supply is unusually inelastic, and vice versa. However, in long windows, individual stocks’ demand and supply elasticities correlate positively. Notably, both fall about 40% with the 1997 Asian Financial Crisis, and remain depressed long after the market and macroeconomic variables recover. A parsimonious model explains both findings with investor information heterogeneity and risk-aversion parameters, fixed in the short-run, being permanently shifted by the crisis.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.350
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.097
GPT teacher head0.274
Teacher spread0.177 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2015
Admission routes1
Has abstractyes

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