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.
Contents
- One factor model
- Two factor model
- Analysis of the one factor model
- Bond pricing using the HullWhite model
- Derivative pricing
- Monte Carlo simulation trees and lattices
- References
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.
One-factor model
The model is a short-rate model. In general, it has dynamics
There is a degree of ambiguity amongst 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 hierarchy has
θ has t dependence – the Hull-White modelθ and α also time-dependent – the extended Vasicek modelTwo-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:
where
Analysis of the one-factor model
For the rest of this article we assume only
θ is calculated from the initial yield curve describing the current term structure of interest rates. Typically α is left as a user input (for example it may be estimated from historical data). σ is determined via calibration to a set of caplets and swaptions readily tradeable in the market.
When
which has distribution
where
When
which has distribution
Bond pricing using the Hull–White model
It turns out that the time-S value of the T-maturity discount bond has distribution (note the affine term structure here!)
where
Note that their terminal distribution for P(S,T) is distributed log-normally.
Derivative pricing
By selecting as numeraire the time-S bond (which corresponds to switching to the S-forward measure), we have from the fundamental theorem of arbitrage-free pricing, the value at time 0 of a derivative which has payoff at time S.
Here,
Thus it is possible to value many derivatives V dependent solely on a single bond P(S,T) analytically when working in the Hull–White model. For example in the case of a bond put
Because P(S,T) is lognormally distributed, the general calculation used for Black-Scholes shows that
where
and
Thus today's value (with the P(0,S) multiplied back in) is:
Here σP is the standard deviation of the log-normal distribution for P(S,T). A fairly substantial amount of algebra shows that it is related to the original parameters via
Note that this expectation was done in the S-bond measure, whereas we did not specify a measure at all for the original Hull-White process. This does not matter — the volatility is all that matters and is measure-independent.
Because interest rate caps/floors are equivalent to bond puts and calls respectively, the above analysis shows that caps and floors can be priced analytically in the Hull–White model. Jamshidian's trick applies to Hull-White (as today's value of a swaption in HW is a monotonic function of today's short rate). Thus knowing how to price caps is also sufficient for pricing swaptions.
The swaptions can also be priced directly as described in Henrard (2003). The direct implementation is usually more efficient.
Monte-Carlo simulation, trees and lattices
However, valuing vanilla instruments such as caps and swaptions is useful primarily for calibration. The real use of the model is to value somewhat more exotic derivatives such as bermudan swaptions on a lattice, or other derivatives in a multi-currency context such as Quanto Constant Maturity Swaps, as explained for example in Brigo and Mercurio (2001). The efficient and exact Monte-Carlo simulation of the Hull-White model with time dependent parameters can be easily performed, see Ostrovski (2013) and (2016).