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Record W3123985161 · doi:10.1177/0148558x11409159

Conflict of interest reforms and analysts’ research biases

2011· article· en· W3123985161 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTSpace · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of Toronto
FundersUniversity of Hong KongChulalongkorn UniversityCity University of Hong KongResearch Foundation of CFA Institute
KeywordsEarningsOptimismProfitability indexStock (firearms)Investment decisionsInvestment bankingEconomicsInvestment (military)BusinessMonetary economicsFinanceBehavioral economicsPolitical science

Abstract

fetched live from OpenAlex

This study examines the consequences of the series of reforms targeting investment banking–related conflicts of interest. The authors compare and contrast optimism biases in analysts’ stock recommendations and earnings forecasts across different types of analyst firms in the postreform period of 2004 to 2007 versus the prereform period of 1998 to 2001. The authors document a significant reduction in the relative optimism of sanctioned investment bank analysts’ stock recommendations but not in their earnings forecasts. Moreover, the authors find little change in the profitability of their stock recommendations but detect a drop in the accuracy of earnings forecasts made by investment bank analysts. In sum, the reforms achieve the objective of mitigating the apparent optimism in investment bank stock recommendations, but they do not provide benefit to investors in terms of more profitable recommendations or more accurate earnings forecasts.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.506
GPT teacher head0.375
Teacher spread0.131 · 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