MAXIMIZING THE GROWTH RATE UNDER RISK CONSTRAINTS
Why this work is in the frame
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Bibliographic record
Abstract
We investigate the ergodic problem of growth‐rate maximization under a class of risk constraints in the context of incomplete, Itô‐process models of financial markets with random ergodic coefficients. Including value‐at‐risk , tail‐value‐at‐risk , and limited expected loss , these constraints can be both wealth‐dependent (relative) and wealth‐independent (absolute). The optimal policy is shown to exist in an appropriate admissibility class, and can be obtained explicitly by uniform, state‐dependent scaling down of the unconstrained (Merton) optimal portfolio. This implies that the risk‐constrained wealth‐growth optimizer locally behaves like a constant relative risk aversion (CRRA) investor, with the relative risk‐aversion coefficient depending on the current values of the market coefficients.
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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 | 0.002 | 0.003 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it