Strategy #0000000046 · Model pricing and relative value
Term-structure model relative value
Estimate a term-structure model, position against the market-model residual, and treat convergence as an assumption.
A trader may model a futures curve with a mean-reverting or multi-factor process and compare market prices with model values. A residual merits investigation only when calibration is credible, signal data are point-in-time and trading costs are realistic. This tool reduces the setup to market price, model price and assumed convergence; it does not estimate OU parameters or optimal entry/exit boundaries.
A model residual can reflect regime change or misspecification; it is not proof of mispricing or mean reversion.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
When a futures price differs from a model value, what relative-value scenario follows from assumed convergence?
Rose enters a model fair value and current futures price, first matching contract month, delivery terms and timestamps.
If the market is below model value, the simplified position is long; if above, it is short. Jack enters an assumed convergence fraction rather than treating the full residual as a profit target.
The model may omit inventories, convenience yield, term premia or regime change. Backtests and risk limits must address stops, leverage, rolls and prolonged divergence.
- Model fair-value assumptionEnter market and model prices, assumed convergence, direction, notional and costs to estimate residual-convergence P&L.
- Market futures price assumptionNo futures-curve calibration, OU parameters, executable prices, risk limits or historical sample; convergence is entirely assumed.
- 50% assumed convergence less costIllustrative expiry outcome.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
dX_t=\kappa(a-X_t)dt+\sigma dW_t,\quad PnL\approx -q(P_{mkt}-P_{model})c-C
κ is mean-reversion speed, a the long-run level and σ volatility; c is assumed convergence and q represents position direction and size. The P&L relation is only a linear scenario approximation.
Greeks: the directional intuition
- 模型風險
- Measures sensitivity to implied volatility.
- 均值漂移
- Measures sensitivity to implied volatility.
- 交易執行
- Measures sensitivity to implied volatility.
dX_t=\kappa(a-X_t)dt+\sigma dW_t,\quad PnL\approx -q(P_{mkt}-P_{model})c-C
Practical context · published observations
Term-structure model relative value: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
沒有校準期貨曲線、OU 參數、成交價格、風險限額或歷史樣本；收斂比例完全是假設。 Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Related methods change the mechanism or risk.
Compare their signal, hedge and model assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Schwartz–Smith two-factor | Short mean reversion plus long-run random level | Separates short shocks from long-term equilibrium changes. | Factor estimation and tenor identification risk. |
| Regime-switching VIX model | Volatility-state switching | Changes VIX futures reversion by market regime. | Delayed state detection and parameter drift. |
| Optimal double stopping | Entry and exit boundaries | Derives entry and exit rules as stopping decisions. | Transaction costs and boundary-estimation error. |
No futures-curve calibration, OU parameters, executable prices, risk limits or historical sample; convergence is entirely assumed.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.