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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. [1] The first application to option pricing was by Phelim Boyle in 1977 (for European options ).
Monte Carlo:methodologies and applications for pricing and risk management. Risk. Paul Glasserman (2003). Monte Carlo methods in financial engineering. Springer-Verlag. ISBN 0-387-00451-3. John C. Hull (2000). Options, futures and other derivatives (4th ed.). Prentice Hall. ISBN 0-13-015822-4. Peter Jaeckel (2002). Monte Carlo methods in ...
Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one time, or once at many different times, and assigning values less than or equal to 0.50 as heads and greater than 0.50 as tails, is a Monte Carlo simulation of the behavior of repeatedly tossing a coin.
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Monte Carlo: methodologies and applications for pricing and risk management. Risk. ISBN 1-899332-91-X. Paul Glasserman (2003). Monte Carlo methods in financial engineering. Springer-Verlag. ISBN 0-387-00451-3. Peter Jaeckel (2002). Monte Carlo methods in finance. John Wiley and Sons. ISBN 0-471-49741-X. Don L. McLeish (2005).
Monte Carlo methods in finance allow financial analysts to construct "stochastic" or probabilistic corporate finance models, as opposed to the traditional static and deterministic models; [66] see Corporate finance § Quantifying uncertainty.
Pages in category "Monte Carlo methods in finance" The following 22 pages are in this category, out of 22 total. This list may not reflect recent changes. ...
As above, the PDE is expressed in a discretized form, using finite differences, and the evolution in the option price is then modelled using a lattice with corresponding dimensions: time runs from 0 to maturity; and price runs from 0 to a "high" value, such that the option is deeply in or out of the money. The option is then valued as follows: [5]