RETRACTED: Entropy-based financial asset pricing: Evidence from Pakistan
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Entropy is an alternative measure to calculate the risk, simplify the portfolios and equity risk premium. It has higher explanatory power than capital asset price model (CAPM) beta. The comparison of Entropy and CAPM beta provide in depth analysis about the explanatory power of the model that in turn help investor to make right investment decisions that minimizes risk. In this context, this study aims to compare Shannon and Rennyi Entropies with the CAPM beta for measuring the risk. Ordinary Least square approach has been utilized using a dataset of 67 enterprises registered in Pakistan Stock exchange. The comparative analysis of CAPM beta and entropy has been carried out with the R2 parameters. The result indicates that entropy has more explanatory power as compare to CAPM beta's explanatory power, and this turns out to be the best option to evaluate the risk performances. The result implies that an investor should make the best investment decision by choosing an enterprise that provide with good returns at minimum risk based on entropy technique.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".