Pricing KTB Futures: An Application of Black-Karasinski Model
Bibliographic record
Abstract
Traditionally, people values KTB futures contracts using the model based on the cost-of-carry argument. However, the underlying commodity for the KTB futures is non-tradable, and so the cost of carry argument cannot be applied to the KTB futures. This paper regards KTB futures contracts as interest-rate derivatives, and prices them using the Black-Karasinski (B-K) term structure model. This paper documents that (1) the market prices of KTB futures are more close to B-K model price than the price by the cost-of-carry argument, though the KTB futures are generally underpriced in the market even under the B-K model; (2) The extent of underpricing is a decreasing function of the remaining maturity of the futures, and becomes smaller recently; (3) The cost of carry argument relatively overprices the KTB futures, and the degree of overpricing is a decreasing function of interest rates and the remaining maturity of the futures; (4) The daily resettlement in the futures contracts affects the futures price very little; (5) The trading strategies based on the theoretical pricing models produce very high trading profit.
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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 | 0.000 | 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 | 0.000 |
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".