Lattice model (finance)
- For other meanings, see lattice model (disambiguation)
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The model divides time between now and the option's expiration into N discrete periods. At the specific time n, the model has a finite number of outcomes at time n + 1 such that every possible change in the state of the world between n and n + 1 is captured in a branch. This process is iterated until every possible path between n = 0 and n = N is mapped. Probabilities are then estimated for every n to n + 1 path. The outcomes and probabilities flow backwards through the tree until a fair value of the option today is calculated.
Equity and commodity derivatives
The simplest lattice model for options on equity and commodities is the binomial options pricing model, while a more sophisticated variant is the Trinomial tree. As above, these models trace the evolution of the option's key underlying variable(s) in discrete-time, starting with today's spot price, and consistent with its volatility; log-normal Brownian motion with constant volatility is usually assumed.
Lattice models are particularly useful in valuing American options, where the choice whether to exercise the option early, or to hold the option, may be modeled at each discrete time/price combination; this is true also for Bermudan options. See Binomial options pricing model#Method. For similar reasons, real options and employee stock options are often modeled using a lattice framework, though with modified assumptions. Some exotic options, such as barrier options, are also easily modeled here; note though that for other Path-Dependent Options, simulation would be preferred.
When it is important to incorporate the volatility smile, or surface, Implied trees can be constructed. Here, the tree is solved such that it successfully reproduces selected (all) market prices, across various strikes and expirations; see local volatility. Using the calibrated lattice one can then price options with strike / maturity combinations not quoted in the market, such that these prices are consistent with observed volatility patterns. Both Implied binomial trees (often Rubinstein IBTs ) and Implied trinomial trees (often Derman-Kani-Chriss ) exist. The former is easier built, but is consistent with one maturity only; the latter will be consistent with, but at the same time requires, known (or interpolated) prices at all time-steps. Edgeworth Binomial Trees  allow for a specified skew and kurtosis in the spot price; for American options, this Edgeworth-generated ending distribution may then be combined with a Rubinstein implied tree.
Interest rate derivatives
For interest rate derivatives, the lattice is built by discretizing either a short-rate model, such as Hull-White or Black Derman Toy, or a forward rate-based model, such as the LIBOR market model or HJM. As for equity, trinomial trees may also be employed for these models; this is usually the case for Hull-White trees.
The short-rate lattices are, in turn, further categorized: these will be either equilibrium-based (Vasicek and CIR) or arbitrage-free (Ho–Lee and subsequent). This distinction means that for equilibrium-based models the yield curve is an output from the model, while for arbitrage-free models the yield curve is an input to the model.
In the latter case, one "calibrates" the model parameters to fit both the current term structure of interest rates (i.e the yield curve), and the corresponding volatility structure. Here, calibration means that the interest-rate-tree reproduces the prices of the zero-coupon bonds (and any other interest-rate sensitive securities) used in constructing the yield curve (note the analog to implied trees above). Once calibrated, the lattice can value a variety of more complex securities and derivatives. See Interest rate derivative#Exotic derivatives. The volatility structure — i.e. vertical node-spacing — here is usually based on interest rate caps, using volatility as implied by the Black-76-prices for each component caplet. For models assuming a normal distribution (such as Ho-Lee), calibration may be performed analytically, while for log-normal models the calibration is via a root-finding algorithm; see under Black–Derman–Toy model.
For the forward rate-based models, dependent on volatility assumptions, the lattice might not recombine. This means that an "up-move" followed by a "down-move" will not give the same result as a "down-move" followed by an "up-move". In this case, the Lattice is sometimes referred to as a bush, and the number of nodes grows exponentially as a function of number of time-steps.
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