La programmation déterministe du budget de capital : un modèle financier
Bibliographic record
Abstract
The financial model presented in the article attempts to further integrate capital budgeting into the firm's overall financial planning policy. Although it is an extension and generalization of Bernhard and Weingartner's previous models, it differs from these works by some basic assumptions related to both the objective function and constraint set. First, the objective function stresses the growing role of managerial discretion as opposed to the common assumption of maximizing shareholders' wealth. In particular we assume that managers wish to maximize the size of the firm under their control at the end of some future time horizon. Since net cash flows of the investment projects selected are sources of future investment funds, the managers try to keep the shareholders' dividends to a minimum level, sufficient enough however to pacify them. Secondly, the model constraints embody the complete set of financial instruments available to the corporation managers: in a sense, this enlarges the previous models' short-term external financing facilities by considering simultaneously the alternative long-term external financial instruments, namely equity and bond issues. In the latter case, the refunding features are incorporated in the constraints. The constraints also imply that managers prefer steady growth of net cash flows through time. This contrasts with the usual maximization approach which has been shown to favor long-term investment projects with somewhat more erratic net cash flows. The derivation of the Kuhn and Tucker conditions for the model allows us to show the impact of the opportunity cost of the various instruments on that of the liquidity requirement and the investment projects selection criterion. Finally, the duality properties also highlight the reciprocal relationships existing between the various opportunity costs, both internal and external.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".