Information Asymmetry and Voluntary <scp>SFAS</scp> 157 Fair Value Disclosures by Bank Holding Companies During the 2007 Financial Crisis
Bibliographic record
Abstract
Abstract We hand‐collect SFAS 157 voluntary fair value disclosures of 18 bank holding companies. The SEC 's Division of Corporate Finance likely targeted these entities in 2008 through their “Dear CFO ” letters in which they requested specific, additional disclosure items. We collect disclosures that match the SEC recommendations and create eight common factor disclosure variables to examine the effect of such disclosures on information asymmetry. We find that disclosure variables about the use of broker quotes or prices from pricing services and the use of market indices and illiquidity adjustments are related to lower information asymmetry. However, disclosure variables about valuation techniques and asset‐backed securities are related to greater information asymmetry. We also document that disclosure complexity, and disclosure tone (uncertainty and litigious) is related to greater information asymmetry. These findings are consistent with criticism that corporate disclosures are voluminous; management may obfuscate unfavorable information which in turn increases market participants’ assessment of uncertainty associated with the fair value measures. We caveat that the setting of the financial crisis and a small sample size may limit the ability to generalize these inferences to other time periods or other financial firms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".