The Black model is widely used for options on
futures and
forwards in commodity and fixed income markets.
Futures and commodity options In commodity and financial futures markets the Black model underlies the pricing of exchange traded and over the counter options on futures. Examples include options on crude oil futures, metal futures and equity index futures. Exchanges and dealers often treat the volatility parameter in the Black formula as the primary quoted quantity and convert between option prices and so called Black implied volatilities when comparing contracts with different strikes and maturities. Volatility surfaces built from these implied volatilities provide a way to summarise option prices across a range of expiries and strike levels.
Caps, floors and bond options In fixed income markets the Black framework is used for
bond options and for
caps and floors. A cap or floor can be decomposed into individual caplets or floorlets. Each component has a payoff that depends on a single forward interest rate over a specified accrual period. Under the assumption that the relevant forward rate is log-normal under an appropriate pricing measure each caplet or floorlet is valued by applying the Black formula to that forward rate and scaling by the notional and accrual factor. Market participants quote cap and floor prices in terms of Black implied volatilities for standard maturities and strike levels.
Swaptions and forward rate models European
swaptions are treated in a similar spirit. The underlying variable is a forward swap rate and prices for swaptions across different maturities and tenors are commonly quoted in terms of Black implied volatilities. In
log-normal forward rate models the Black formula remains the basic building block for valuing individual caplets, floorlets and swaptions. The model specifies joint dynamics for a family of forward rates and is calibrated so that it reproduces observed Black or normal implied volatility surfaces used in swaption and cap markets.
Inflation-linked caps and floors on RPI for pension increases In the United Kingdom many defined benefit pension schemes provide increases that are linked to the
RPI or
CPI, subject to an annual floor and cap, a structure known as
limited price indexation and often written as LPI(a,b). A typical benefit might promise annual increases in line with RPI subject to a floor of 0\% and a cap of 5\%, denoted LPI(0,5). These guarantees can be valued or hedged using inflation derivatives such as RPI swaps and inflation caps and floors. For a single year let I denote the random annual RPI inflation rate expressed as a proportion. With a floor a and cap b on the annual increase the limited price indexation rate can be written as : L(I) = \min\bigl(\max(I,a), b\bigr). Using the notation x^+ = \max(x,0) this decomposes as : L(I) = I - (I - b)^+ + (a - I)^+. The second term removes outcomes where inflation is above the cap, and the third term replaces very low inflation outcomes with the floor level. To obtain a tractable formula, assume that under a pricing measure the one year inflation rate I is strictly positive and log normal with forward mean F, volatility \sigma and time to maturity T. This is the same log normal setup used earlier for the Black formula, with F playing the role of the forward price and the cap and floor strikes playing the role of the option strike. Under this assumption : \mathbb{E}[L(I)] = F - \mathbb{E}\bigl[(I - b)^+\bigr] + \mathbb{E}\bigl[(a - I)^+\bigr]. For a strike K define : d_1^{(K)} = \frac{\ln(F/K) + \tfrac{1}{2}\sigma^2 T}{\sigma \sqrt{T}}, \quad d_2^{(K)} = d_1^{(K)} - \sigma \sqrt{T}, and let N denote the cumulative distribution function of a standard normal random variable. Ignoring discounting over a single year, the corresponding call and put expectations are : \mathbb{E}\bigl[(I - K)^+\bigr] = F N\bigl(d_1^{(K)}\bigr) - K N\bigl(d_2^{(K)}\bigr), : \mathbb{E}\bigl[(K - I)^+\bigr] = K N\bigl(-d_2^{(K)}\bigr) - F N\bigl(-d_1^{(K)}\bigr), which mirror the Black call and put formulas in the formula section, with the exponential discount factor omitted for simplicity. For general LPI(a,b) this gives : \mathbb{E}[L(I)] = F - \bigl(F N\bigl(d_1^{(b)}\bigr) - b N\bigl(d_2^{(b)}\bigr)\bigr) + \bigl(a N\bigl(-d_2^{(a)}\bigr) - F N\bigl(-d_1^{(a)}\bigr)\bigr), where d_1^{(a)}, d_2^{(a)} use strike a and d_1^{(b)}, d_2^{(b)} use strike b. As an illustration consider a one year LPI(0,5) structure with a forward RPI inflation rate of 3.5\%, so F = 0.035, a cap b = 0.05, a floor a = 0, volatility parameter \sigma = 0.02 and T = 1. Under the log normal model the floor term is zero, since I is strictly positive, and : \mathbb{E}[L(I)] = F - \bigl(F N\bigl(d_1^{(0.05)}\bigr) - 0.05 N\bigl(d_2^{(0.05)}\bigr)\bigr). With F substantially below the cap relative to the assumed log normal volatility, the cap rarely bites, the call term is very small, and the expected LPI(0,5) increase is therefore very close to the forward inflation rate of 3.5\%. It is common to approximate the one year inflation rate by a normal random variable, in line with the
Bachelier model, especially when negative inflation is considered. Under that normal model, with the same central assumption F = 3.5\%, volatility \sigma = 2\% and LPI(0,5), the expectation \mathbb{E}[L(I)] is lower, approximately 3.27\%, because both the cap at 5\% and the floor at 0\% are active over a wider range of outcomes. ==Limitations and extensions==