Does the Method of Entry Matter? Evidence from Indian Adr and Gdr Issues
Bibliographic record
Abstract
This paper documents changes in volatility, returns, liquidity and valuation on the local market following different ADR issues, viz., Level I, II, III, Rule 144A and Regulation S offerings, by the Indian firms in the global market. The sample consists of 84 ADR and GDR issues made by the Indian firms during 1990-2001. The Rule 144A and Reg S issues experience a significant decline in volatility on the home (Indian) market and these effects are mainly observed during the first sub-period, 1990-1997. In addition, Level III ADRS, which are exchange listed and capital raising issues, experience a significant increase in liquidity on the home market and these occur in the second sub-period 1998-2001. Though ADRs in general experience an increase in valuation (as measured by the q ratios) after the U.S. issue, there is no strong evidence to suggest that the magnitude of increase depends on the method of entry.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".