A Relação entre o Risco e as Práticas de Governança Corporativa Diferenciada no Mercado Brasileiro de Ações: uma abordagem sob a égide da teoria dos portfólios de Markowitz
Bibliographic record
Abstract
This study examines whether there is a relationship between the risk of a portfolio that would be sufficiently diversified in the Brazilian stock market, made by companies classified in the IGC, in comparison with the Market Portfolio. For this purpose, a preliminary proceeding of the methodological research literature, documentary exploratory and subsequent research of the theoretical portfolio of the index shares differentiated corporate governance of BM&FBOVESPA valid for first, second and third quarters of 2009. Therefore, with the aid of the electronic spreadsheet Excel, being used with the model of Markowitz (1952) and of the methodology developed by Gonçalves Jr, Pamplona and Montevechi (2002), we have attempted to find the minimum variance portfolios for each quarter in order to test the hypothesis that there is a relationship between the risk of these portfolios, considered sufficiently diversified in the Brazilian stock market (according to the findings of Sanvicente and Bellato, 2004), composed by companies classified in the IGC. The results have indicated that these portfolios for the assets of IGC, are higher than the market portfolio, since they would have their risks represented by about 34%, 32% and 21% of risk IBOVESPA in its corresponding period in identical levels of return. Through the theory of diversification is possible to obtain an inverse relationship between risk and good corporate governance practices. Additionally, the IGC selected portfolio dominates the portfolio of the IGC and the Bovespa index, respectively, using the coefficient of variation, it has the lowest risk contained for each additional return
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".