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Hull–White model

Hull–White model is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Hull–White model rather than just read about it. In short: In financial mathematics, the Hull–White model is a model of future interest rates. In its most generic formulation, it belongs to the class of no-arbitrage models that are able to fit today's term structure of interest rates.

Key takeaways

  • Hull–White model belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Hull–White model to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Hull–White model from memory before moving on to harder problems.

Reference excerpt

In financial mathematics, the Hull–White model is a model of future interest rates. In its most generic formulation, it belongs to the class of no-arbitrage models that are able to fit today's term structure of interest rates. It is relatively straightforward to translate the mathematical description of the evolution of future interest rates onto a tree or lattice and so interest rate derivatives such as bermudan swaptions can be valued in the model. The first Hull–White model was described by John C. Hull and Alan White in 1990. The model is still popular in the market today.

The model

One-factor model The model is a short-rate model. In general, it has the following dynamics:

d r ( t ) = [ θ ( t ) − α ( t ) r ( t ) ] d t + σ ( t ) d W ( t ) . {\displaystyle dr(t)=\left[\theta (t)-\alpha (t)r(t)\right]\,dt+\sigma (t)\,dW(t).}

There is a degree of ambiguity among practitioners about exactly which parameters in the model are time-dependent or what name to apply to the model in each case. The most commonly accepted naming convention is the following:

θ {\displaystyle \theta } has t (time) dependence — the Hull–White model.

θ {\displaystyle \theta } and α {\displaystyle \alpha } are both time-dependent — the extended Vasicek model.

Two-factor model The two-factor Hull–White model (Hull 2006:657–658) contains an additional disturbance term whose mean reverts to zero, and is of the form:

d f ( r ( t ) ) = [ θ ( t ) + u − α ( t ) f ( r ( t ) ) ] d t + σ 1 ( t ) d W 1 ( t ) , {\displaystyle d\,f(r(t))=\left[\theta (t)+u-\alpha (t)\,f(r(t))\right]dt+\sigma _{1}(t)\,dW_{1}(t),}

where f {\displaystyle \displaystyle f} is a deterministic function, typically the identity function (extension of the one-factor version, analytically tractable, and with potentially negative rates), the natural logarithm (extension of the Black–Karasinski model, not analytically tractable, and with positive interest rates), or combinations (proportional to the natural logarithm on small rates and proportional to the identity function on large rates); and u {\displaystyle \displaystyle u} has an initial value of 0 and follows the process:

d u = − b u d t + σ 2 d W 2 ( t ) {\displaystyle du=-bu\,dt+\sigma _{2}\,dW_{2}(t)}

Analysis of the one-factor model For the rest of this article we assume only θ {\displaystyle \theta } has t-dependence. Neglecting the stochastic term for a moment, notice that for α > 0 {\displaystyle \alpha >0} the change in r is negative if r is currently "large" (greater than θ ( t ) / α ) {\displaystyle \theta (t)/\alpha )} and positive if the current value is small. That is, the stochastic process is a mean-reverting Ornstein–Uhlenbeck process. θ is calculated from the initial yield curve describing the current term structure of interest rates. For constant α {\displaystyle \alpha } and σ {\displaystyle \sigma } , the time-dependent drift can be determined explicitly from the initial term structure. Let P M ( 0 , T ) {\displaystyle P^{M}(0,T)} denote the market price at time 0 of a zero-coupon bond maturing at T {\displaystyle T} , and define the market instantaneous forward rate by

f M ( 0 , T ) = − ∂ ∂ T ln ⁡ P M ( 0 , T ) . {\displaystyle f^{M}(0,T)=-{\frac {\partial }{\partial T}}\ln P^{M}(0,T).}

An exact fit to the initial term structure is obtained by choosing

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Hull–White model

Start with the simplest possible case. Write down what Hull–White model claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Hull–White model before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Hull–White model ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Hull–White model

In research
Hull–White model appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Hull–White model in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Hull–White model is common in secondary-school and first-year university syllabi. It links to neighbouring topics Financial models, Fixed income analysis, Interest rates, so understanding it makes those chapters shorter.
In everyday life
Look for Hull–White model outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Hull–White model in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Hull–White model means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Hull–White model out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Hull–White model in simple terms?

In financial mathematics, the Hull–White model is a model of future interest rates. In its most generic formulation, it belongs to the class of no-arbitrage models that are able to fit today's term structure of interest rates.

Why does Hull–White model matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Hull–White model?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Hull–White model.

Tags

  • Financial models
  • Fixed income analysis
  • Interest rates
  • Short-rate models

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