Characteristics of Observed Limit Order Demand and Supply Schedules for Individual Stocks
Bibliographic record
Abstract
Using complete order books from the Korea Stock Exchange for a four-year period including the 1997 Asian financial crisis, we observe (not estimate) limit order demand and supply curves for individual stocks.Both curves have demonstrably finite elasticities.These fall markedly, by about 40%, with the crisis and remain depressed long after other economic and financial variables revert to pre-crisis norms.Superimposed upon this common long-term modulation, individual stocks' supply and demand elasticities correlate negatively at high frequencies.That is, when a stock exhibits an unusually elastic demand curve, it tends simultaneously to exhibit an unusually inelastic supply curve, and vice versa.These findings have potential implications for modeling how information flows into and through stock markets, how limit order providers react or interact to information flows, how new information is capitalized into stock prices, and how financial crises alter these processes.We advance speculative hypotheses, and invite further theoretical and empirical work to explain these findings and their implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".