An Empirical Test of a Two-Factor Mortgage Valuation Model: How Much Do House Prices Matter?
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Bibliographic record
Abstract
This article develops a two-factor structural mortgage pricing model in which rational mortgage-holders choose when to prepay and default in response to changes in both interest rates and house prices. We estimate the model using comprehensive data on the pool-level termination rates for Freddie Mac Participation Certificates issued between 1991 and 2002. The model exhibits a statistically and economically significant improvement over the nested one-factor (interest-rate only) model in its ability to match historical prepayment data. Moreover, the two-factor model produces origination prices that are significantly closer to those quoted in the to-be-announced market than the one-factor model. Our results have important implications for hedging mortgage-backed securities.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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