On the valuation of psychic returns to art market investments
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
Investing in art objects yields financial and psychic returns. The psychic returns arise since art has a superior consumption good aspect as well. The question is whether it is possible to measure the psychic returns. One valuation method for estimating the psychic returns to investing in artworks is their rental price. Here, we make use of the prices charged by a Canadian fine art company for its art rental services and calculate the implied psychic returns to be about 28 percent. Next, we review the finance-theoretic approaches to measuring the psychic returns to investing in artworks. We follow Hodgson and Vorkink’s (2004, Canadian Journal of Economics) suggestion that the alpha parameter in the CAPM captures the extent of net psychic returns. The evidence on alpha from the art market applications of the CAPM coupled with the transaction cost data from international art auctions also suggests that the psychic returns to investing in artworks might amount to about 28 per cent.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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