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Worst-of option

A worst-of option selects the weakest contract-defined asset outcome. See why a performance call needs both returns above the strike, with a normalized USD payoff example.

A worst-of option bases its payoff on the least favourable of several contract-defined asset outcomes. A long worst-of performance call pays only when the lowest underlying return exceeds its strike. One strong asset cannot rescue a weak one, so a bullish view on the group is insufficient unless the contract's weakest performer also clears the hurdle.
This is a rainbow option. The label identifies a selection rule; the confirmation must still specify what is ranked, the option type, the position and the payment terms. This page uses a long, cash-settled European call on the minimum of two normalized returns.

Normalize before choosing the weakest asset

Consider a synthetic contract with one terminal observation and cash payment one year after inception. Both stock prices are quoted in USD per share. Returns exclude dividends; there is no currency conversion.

AssetInitial pricePrice at one yearSimple price return
AUSD 100USD 120+20%
BUSD 200USD 220+10%
For each asset, its price return is Ri=Si(T)/Si(0)−1R_i=S_i(T)/S_i(0)-1. B is the weaker performer despite its higher share price. Comparing the raw terminal prices would select a different exposure.

Let NN be the USD notional and kk the performance strike, quoted as a decimal return. The long holder receives

Xworst=Nmax⁡(min⁡(RA,RB)−k,0).X_{\mathrm{worst}}=N\max\left(\min(R_A,R_B)-k,0\right).
Set N=1,000N=1{,}000 and k=0.05k=0.05. B's 10%10\% return exceeds the 5%5\% strike by 5 percentage points, giving a terminal payoff of USD 50. The matching best-of call selects A's return and pays USD 150 under the same terms.
If B instead ends at USD 180, its return is −10%-10\%. The worst-of call then pays zero, even though A still gains 20%20\%. A positive payoff requires both returns to exceed the strike; equality gives zero.
With A's return fixed at plus 20%, a worst-of call on USD 1000 notional and a 5% return strike pays zero when B returns minus 10%, USD 50 when B returns plus 10%, and at most USD 150 once B reaches plus 20%.
With A's return fixed at plus 20%, a worst-of call on USD 1000 notional and a 5% return strike pays zero when B returns minus 10%, USD 50 when B returns plus 10%, and at most USD 150 once B reaches plus 20%.
Original synthetic terminal-payoff curve, holding A's price return at +20%. Cash settlement occurs at the one-year observation; the premium is excluded. The USD 150 ceiling applies to this slice with A fixed, rather than to the contract across all possible outcomes.

Once B outperforms A, A becomes the weakest link. Further gains in B alone cannot increase this payoff. Conversely, improving A while B remains at 10%10\% leaves the USD 50 payoff unchanged.

A useful bound, and a different meaning of “worst”

Write Ci=Nmax⁡(Ri−k,0)C_i=N\max(R_i-k,0) for each individual performance call's cash payoff with the same notional, strike and payment date. Since taking the positive part preserves the ordering,

Xworst=min⁡(CA,CB).X_{\mathrm{worst}}=\min(C_A,C_B).
The worst-of call therefore never pays more than either individual call in a given outcome. This state-by-state bound is useful when checking a payoff implementation; Stulz establishes the corresponding dominance result for calls on asset values. (Stulz, §3.2)
“Worst” refers here to the lowest asset return, not the worst possible financial outcome for every party. A put on that minimum has a different payoff, and selling that put reverses the holder's cash-flow exposure. A structured note can add coupons, barriers, early redemption and principal-repayment rules. None of those features follows from the phrase “worst-of option.”

The USD 1,000 in this example scales the option payment; it is not a deposit returned at maturity or a capital guarantee. USD 50 is a payoff before deducting the option premium and financing costs, so it does not establish a profit.

The missing input in a valuation

The payoff rule can be evaluated from a terminal scenario. Its present value also needs a model for the assets' joint outcomes and discounting. Knowing each asset's separate return distribution does not tell us how often both clear the strike. Correlation helps describe dependence, but a correlation number alone does not specify an arbitrary joint distribution or establish a universal price comparison.
For the joint-model step, §2.1 of Correlated Randoms and Low-Discrepancy Sequences shows how a matrix factorization turns independent normal draws into correlated shocks. The full lesson requires membership and has a public preview. Those shocks can feed a specified multi-asset model; the selection and strike rule above must then be applied to each resulting pair of returns.

Sources

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