Bibliographic record
Abstract
Underlying idiosyncratic and illiquidity risks are suppressed in infrequently reported indexes of house prices and rents. Idiosyncratic risks result from bid–ask spreads for prices and rents. Time series autocovariances generate a distribution of prices and rents. Capital gains and rent-price ratios are transforms of these distributions, generating cross-sectional idiosyncratic volatility. Housing data are infrequent and usually made available every month. The monthly–quarterly volatility ratios of house prices and rents and their spreads estimate unobserved daily fluctuations and illiquidity risks. Including idiosyncratic and illiquidity risks, a U.S. house has a standard deviation in returns of 8.7% annually for three decades after 1990. With a mean excess return of 3.7%, the Sharpe ratio of 0.42 is comparable to the S&P 500. Excluding spreads, the house Sharpe ratio is 0.69. House returns respond to liquidity. A 1% increase in volume raises returns by 0.8%.
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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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".