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How Time-Varying Hull–White Parameters Improve Instrument Pricing Fits

Article Quant Q&A · Author: A.Oreo

Summary

The document explains the roles of time-dependent parameters in the Hull–White short-rate model. A time-varying drift term can fit the initial yield curve, but matching that curve alone does not ensure accurate prices for more complex interest-rate products, such as options. Allowing mean reversion or volatility to vary over time adds flexibility for fitting those instrument prices.

The discussion describes nonstationary volatility as a model structure in which volatility changes over time rather than remaining constant. The answers also relate time-varying mean reversion and volatility to observed differences across maturities and to the evolution of interest-rate models and trees. These are conceptual explanations, not a calibration recipe or empirical comparison. The material does not specify how to estimate the parameter functions, quantify fit improvements, or assess the trade-off introduced by a volatility structure that may differ from today’s market structure in the future.

Key ideas

  • A time-dependent drift term can fit the initial yield curve without fitting prices of more complex instruments.
  • Time-varying mean reversion or volatility adds flexibility for matching interest-rate product prices.
  • Nonstationarity means the model’s volatility structure changes over time.
  • The discussion links time-varying parameters to maturity-dependent market dynamics but gives no calibration procedure.

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Full text
# Time dependent parameters in Hull-White model


# Time dependent parameters in Hull-White model












`Hull-White:` $$d r = [\theta(t) - ar]d t + \sigma d W_t.$$ There is a statement in John Hull's book:

The advantage of making $a$ or $\sigma$, or both, functions of time is that the models can be fitted more precisely to the prices of instruments that trade actively in the market. The disadvantage is that the volatility structure becomes nonstationary. The volatility term structure given by the model in the future is liable to be quite different from that existing in the market today.

$\theta(t)$ can already match the initial curve in the market, what's the meaning of `fitted more precisely to the prices?`

$\sigma(t)$ can match today's implied vol of all maturities, it should be better than $\sigma.$ How to understand `nonstationary?`

## Answer by Daneel Olivaw (score 1)

https://quant.stackexchange.com/a/38747

On your first question, the fact that you fit to the yield curve $-$ which is what the standard Hull-White model with time-dependent $\theta(t)$ allows to do $-$ does not mean that you are fitting the prices of more complex products such as options. For that you need to make $a$ and/or $\sigma$ also time-dependent.

On your second question, it simply means that you no longer have a flat, constant value for $\sigma$ but a much complex structure which depends on time $-$ I don't think there is anything more to that statement.

## Answer by Hui (score 1)

https://quant.stackexchange.com/a/39768

Question 1: I would say these are just assumptions they made based on the observation of real market dynamics, that is, interest rate does show inconstant volatilities and mean reversion on different term structure. Having these variables time-dependent will make the simulated tree better match the real term structure. That's basicly how interest rate trees were gradually changed from Ho-LEE to Hull-white etc.

Question 2: It is indeed non-stationary. In financial markets, any products with term structure(or different expiries) usually show non-stationary volatilities throughout time, such as interest rate, energy, grain or financial futures etc. And most cases, short-term underlying show much higher volatility than longer than longer term. (I know gold is an exception). Interest rate products also show this type of dynamics that the volatility curve normally downward sloped as tenor goes up.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.