Interactive Socially Responsible Portfolio Selection: An Application to the Spanish Stock Market
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
During the late years, given the causes of the 2008 financial crisis, ethical, social, environmental and governance concerns have become relevant investment decision criteria for both individual and institutional investors. However, while a diverse set of models has been developed to support investment decision-making based on financial criteria, models including also socially responsible criteria are rather scarce. The model proposed in this paper is intended to be an individual investment decision making tool for stocks‘ portfolio selection, taking into account the subjective and individual preferences about different financial and socially responsible features of a particular investor. In this sense, the first problem to be solved is the measurement of the social responsibility degree of financial assets. In this work, we propose the construction of synthetic indicators based on the double reference point scheme. Once the social responsibility degree of the assets has been measured, multiple criteria portfolio selection model is formulated, which includes, together with the classical financial criteria, a social responsibility criterion based on the previously obtained synthetic indicators. The resulting model is solved using a mixed reference point – classification scheme. In order to illustrate the suitability of the synthetic indicators built, and the applicability of the proposed investment decision making model, an empirical study on a set of Spanish domiciled stocks is presented.
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.
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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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 it