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In mathematical finance , a Monte Carlo option model uses Monte Carlo methods [Notes 1] to calculate the value of an option with multiple sources of uncertainty or with complicated features. Glasserman showed how to price Asian options by Monte Carlo. Schwartz developed a practical Monte Carlo method for pricing American-style options. In terms of theory , Monte Carlo valuation relies on risk neutral valuation. The technique applied then, is 1 to generate a large number of possible, but random , price paths for the underlying or underlyings via simulation , and 2 to then calculate the associated exercise value i.
This result is the value of the option. Least Square Monte Carlo is used in valuing American options. The technique works in a two step procedure. As can be seen, Monte Carlo Methods are particularly useful in the valuation of options with multiple sources of uncertainty or with complicated features, which would make them difficult to value through a straightforward Black—Scholes -style or lattice based computation.
The technique is thus widely used in valuing path dependent structures like lookback- and Asian options  and in real options analysis. Conversely, however, if an analytical technique for valuing the option exists—or even a numeric technique , such as a modified pricing tree  —Monte Carlo methods will usually be too slow to be competitive.
They are, in a sense, a method of last resort;  see further under Monte Carlo methods in finance. With faster computing capability this computational constraint is less of a concern. From Wikipedia, the free encyclopedia. Alternative Valuation Methods for Swaptions: Valuation of fixed income securities and derivatives , pg.