Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.06272 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917772286492672 |
|---|---|
| author | Decourt, Roberto Frota Almeida, Heitor Protin, Philippe Gonzalez, Matheus R. C. |
| author_facet | Decourt, Roberto Frota Almeida, Heitor Protin, Philippe Gonzalez, Matheus R. C. |
| contents | The purpose of the research was to build an index of informational asymmetry with market and firm proxies that reflect the analysts' perception of the level of informational asymmetry of companies. The proposed method consists of the construction of an algorithm based on the Elo rating and captures the perception of the analyst that choose, between two firms, the one they consider to have better information. After we have the informational asymmetry index, we run a regression model with our rating as dependent variable and proxies used by the literature as the independent variable to have a model that can be used for other researches that need to measure the level of informational asymmetry of a company. Our model presented a good fit between our index and the proxies used to measure informational asymmetry and we find four significant variables: coverage, volatility, Tobin q, and size. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_06272 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Information Asymmetry Index: The View of Market Analysts Decourt, Roberto Frota Almeida, Heitor Protin, Philippe Gonzalez, Matheus R. C. General Finance The purpose of the research was to build an index of informational asymmetry with market and firm proxies that reflect the analysts' perception of the level of informational asymmetry of companies. The proposed method consists of the construction of an algorithm based on the Elo rating and captures the perception of the analyst that choose, between two firms, the one they consider to have better information. After we have the informational asymmetry index, we run a regression model with our rating as dependent variable and proxies used by the literature as the independent variable to have a model that can be used for other researches that need to measure the level of informational asymmetry of a company. Our model presented a good fit between our index and the proxies used to measure informational asymmetry and we find four significant variables: coverage, volatility, Tobin q, and size. |
| title | Information Asymmetry Index: The View of Market Analysts |
| topic | General Finance |
| url | https://arxiv.org/abs/2409.06272 |