Irving Fisher and Financial Economics: The Equity Premium Puzzle, the Predictability of Stock Prices, and Intertemporal Allocation Under Risk
Bibliographic record
Abstract
Irving Fisher is renowned as the pundit who declared in October 1929 that stock prices appeared to have reached a permanently high plateau and who, having amassed a net worth of ten million dollars in the boom of the 1920s, proceeded to lose eleven million dollars of that fortune in the crash, which, as John Kenneth Galbraith (1977, p. 192) remarked, “was a substantial sum, even for an economics professor.” Along with the Dow-Jones index, Fisher's reputation for understanding financial markets declined relative to that of Roger Babson, the stock forecaster, amateur economist, and founder of Babson College, who presciently predicted the stock market crash of autumn 1929 (and, with less prescience, the stock market crashes of 1926, 1927, and 1928, and the stock market recovery of 1930). An editorial in The Commercial and Financial Chronicle (November 9, 1929) declared of Fisher: “The learned professor is wrong as he usually is when he talks about the stock market” (quoted by Galbraith 1972, p. 151).
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".