The role and implications of 'award winning' investor relations practices
Bibliographic record
Abstract
This thesis investigates the concept of Investor Relations (IR), its role within organisations and its capital market implications. The thesis consists of two independent but related empirical chapters. First~ I examine whether IR is successful in insulating firms from negative market shocks. The wave of high profile accounting and corporate governance scandals that occurred in the US during 2001 and 2002 placed corporate credibility under the microscope and led to both a crisis in investor confidence and increased investor scepticism towards the capital market (Allen, 2002; Asthana et aI., 2003; Bratton, 2003; Eduardo et al., 2003; Smith, 2003). Against this backdrop, I find no evidence in support of the prediction that an established reputation for effective IR helped shield firms from the general market fallout during several event windows that fall within this crisis period, October 2001 through September 2002. On the contrary, results suggest that firms with established i:R reputations actually fared worse on a series of market-related dimensions, including more negative returns to news ~ssociated with financial credibility issues, and a significant decline in press coverage, trading volume, and analyst coverage. These results suggest the overall reputation of the IR industry may have been tarnished during this period. Second, I analyse the association b~tween the effectiv~ness of firms' IR practices and various properties of analysts' quarterly earnings forecasts. I find that analysts are able to forecast earnings at the end of a quarter more accurately for effective IR firms compared to other firms, suggesting that IR helps firms increase the total amount of infonnation available to the market about the firm. !Ii addition, I find that analysts are able to forecast earnings at the beginning of the quarter more accurately for effective IR firms compared to other firms, suggesting that IR facilitates the flow of information to investors in a timelier manner. Moreover, I find evidence that finns recognised for their effective IR practices guide analyst's forecasts downwards in order to meet or beat expectations more frequently compared to other firms. Similarly, I fmd that when initial forecasts in a quarter are pessimistic, effective IR finns have a greater walk up of earnings expectations over the quarter compared to other finns. Similarly, I fmd that when initial forecasts in the quarter are optimistic, effective IR firms have a greater walk down of earnings expectations compared to other finns. This suggests that managing analysts' expectations so that they do not diverge .significantly from reality is a very important aspect of investor relations. Finally, there is evidence to show that forecasts for effective IR finns become more accurate and less dispersed over the quarter compared to other firms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".