MORE ON THE ORIGIN OF FINANCIAL ECONOMICS: EARLY CONTRIBUTIONS TO JOINT LIFE ANNUITY VALUATION
Bibliographic record
Abstract
The origin of modern financial economics can be traced to early discounted expected value solutions for the price of life annuities. In contrast to the single life annuity valuations attributed to Jan de Witt and Edmond Halley, the computational complexity of joint life annuity valuation posed difficulties. Following a brief review of various joint life annuity specifications, a history of joint life annuity issuance and valuation in northern Europe from the thirteenth to the mid-eighteenth centuries is provided. With this background, the 1671 correspondence from de Witt to Jan Hudde on possible methods for valuing joint life annuities is detailed. These methods are contrasted with the geometric method described in Halley (1693), providing impetus for examination of the analytical approximations developed by Abraham de Moivre and Thomas Simpson.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".