Rainbow option

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A single option linked to two or more underlying assets. In order for the option to pay off, all the underlying assets must move in the intended direction.

Investopedia Says:
The underlying securities can have different characteristics, such as expiry date and strike price, but all must move in the way the option holder has bet they will.

Here's a sports-betting analogy that demonstrates a rainbow option: suppose you're at a baseball tournament with three fields backing one another. One game is halfway through, a second is just starting and a third starts in an hour. A type of bet that's analogous to a rainbow option is one that earns you a profit if you pick all three winners, but gets you  nothing if any one team you pick is a loser.

Related Links:
An introduction to the world of options, covering everything from primary concepts to how options work and why you might use them. Options Basics Tutorial


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Rainbow option is a derivative exposed to two or more sources of uncertainty,[1] as opposed to a simple option that is exposed to one source of uncertainty, such as the price of underlying asset. Rainbow options are usually calls or puts on the best or worst of n underlying assets, or options which pay the best or worst of n assets. The number of assets underlying the option is called the number of colours of the rainbow.[2] The options are often considered a correlation trade since the value of the option is sensitive to the correlation between the various basket components.

Rainbow options are used, for example, to value natural resources deposits. Such assets are exposed to two uncertainties—price and quantity.

Some simple options can be transformed into more complex instruments if the underlying risk model that the option reflected does not match a future reality. In particular, derivatives in the currency and mortgage markets have been subject to liquidity risk that was not reflected in the pricing of the option when sold.

Pricing and Valuation

Rainbow options are usually priced using an appropriate industry-standard model (such as Black–Scholes) for each individual basket component, and a matrix of correlation coefficients applied to the underlying stochastic drivers for the various models. While degenerate cases have simpler solutions, the general case must be approached with Monte Carlo methods.

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