The Impact of Expertise and Investment Familiarity on Investors' Use of Online Financial Report Information
Bibliographic record
Abstract
In this study we use a unique dataset to examine whether professional and nonprofessional investors use different online quarterly financial information when making investment decisions, and whether the online information they use depends on whether they are researching a new investment or evaluating a current investment. Our results suggest professional investors prefer to view PDF-formatted quarterly reports and tend to rely directly on the financial statements compared to nonprofessional investors who prefer to view HTML-formatted reports and have a tendency to rely more on management's discussion of the quarter's results. Our results also suggest that for nonprofessional investors, investment familiarity (i.e., whether they are evaluating a current investment or researching a new investment) strongly impacts the type of financial information they view within a firm's quarterly reports. Our results have implications for the design of experimental studies, and provide information useful to managers, financial report users, standard setters, and researchers as they attempt to better understand the types of information that professional and nonprofessional investors use when making investment decisions.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".