Do Investment Funds Audited by the Big Four Firms Exhibit Different Performances? Evidence from Brazil
Bibliographic record
Abstract
Investment funds manage a portfolio composed of financial instruments; therefore, their accounting reports should undergo a careful process of preparation and auditing. The main purpose of this study is to analyze the effect of being audited by a Big Four audit company on funds’ risk-adjusted performance. The database is composed of equity funds from the Brazilian financial market, with daily returns spanning from January 2005 to March 2023. The funds’ performance was measured based on three indicators, including the Sharpe Ratio and Jensen’s Alpha. Fama and MacBeth regressions were used to test the hypotheses. The main findings indicate that the benefits of audit quality also include a positive effect on the risk-adjusted performance of investment funds, as the coefficient of the variable “Big Four” was positive and significant based on the proxies for risk-adjusted performance. This study advances this area of research by demonstrating the effects of the type of audit on the risk-adjusted performance indicators of investment funds.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".